Cross-Chain Technology of Consortium Blockchain Based on Identity Authentication

Abstract

With consortium blockchain becoming the mainstream form of blockchain applied to various industries, the proportion of nonasset data in blockchain applications is gradually increasing. However, there is currently no cross-chain solution for nonasset data. The aim of this study is to explore the cross-chain problem of nonasset data and design a cross-chain solution that is suitable for the application scenarios of consortium blockchains. We achieved cross-chain identity authentication through an integrated distributed trust model. We then proposed cross-chain anchor nodes as alternatives to traditional routing, eliminating third-party Relay risks while ensuring secure information transmission through smart contracts. Finally, on the basis of ensuring the timeliness and reliability of data transmission, combined with the consortium blockchain organizational structure, cross-chain technology is more in line with the characteristics of data element circulation. This study provides an effective and secure solution for cross-chain interaction and application data flow in consortium blockchains through comprehensive smart contract protection mechanisms and rigorous access controls. The proposed approach is expected to promote the safe application and development of consortium blockchain technology in various industries.

1. Introduction

According to the statistics of the China Academy of Information and Communications Technology, blockchain-related enterprises have continued to increase in recent years. From 2016 to 2021, the average annual number of new blockchain enterprises in the world was about 4700 [1]. In 2022, the number of new blockchain enterprises decreased to about 1400, but there was a big increase in the amount of investment [2]. As of December 2023, there are 10,291 blockchain enterprises in the world [3]. The global blockchain industry pattern is basically stable and has entered a stage of high-quality development.

For example, F2C2T solves the cross-chain consistency problem of linked data assets; however, it cannot be deployed at scale. Although deep learning cross-chain EHR schemes can use deep learning to facilitate cross-chain data transmission, they ignore privacy protection of user data.

With the accelerated application of blockchain in government services, the real economy, and other fields, scenes and model innovation are constantly emerging, and the industry ecology is gradually improving [4]. While existing cross-chain solutions primarily focus on asset transfer scenarios, they fall short in addressing the growing need for efficient and secure nonasset data exchange between consortium blockchains. Current approaches either rely on trusted third parties, introducing security risks and performance bottlenecks, or implement complex routing mechanisms that add significant overhead [5]. Consortium blockchain environments urgently need lightweight, secure, and efficient cross-chain solutions. Current blockchain implementations create isolated data islands, significantly reducing the value of interconnected data [6]. The blockchain is actually a decentralized de-trust network, which guarantees the credibility of data on a single chain through mechanisms like consensus algorithms, but cannot guarantee the credibility of inter-chain data in the process of interconnection, which greatly reduces the use value of blockchain applications. Cross-chain technology has become a key issue to promote the integration and development of the blockchain ecosystem [7].

Current cross-chain solutions primarily target asset transfer scenarios but inadequately address the growing demand for efficient and secure nonasset data exchange between consortium blockchains. Existing approaches either perform the following:

1

Rely on trusted third parties, introducing security vulnerabilities and performance bottlenecks.

2

Implement complex routing mechanisms that create significant operational overhead.

3

Lack specialized protocols for handling diverse data types beyond digital assets.

This creates a pressing need for lightweight, secure, and efficient cross-chain solutions tailored to consortium blockchain environments. As blockchain technology expands beyond financial applications into government services, supply chain management, and industrial applications, isolated blockchain networks increasingly restrict the value potential of interconnected data systems.

This study aims to develop a cross-chain mechanism that facilitates secure nonasset data exchange between consortium blockchains while maintaining their inherent security properties. Specifically, we seek to achieve the following:

1

Design a distributed trust model based on identity authentication that eliminates dependency on third-party intermediaries.

2

Develop lightweight alternatives to traditional cross-chain routing mechanisms.

3

Create a comprehensive framework for secure cross-chain data exchange that preserves blockchain independence.

We make the following three major innovative contributions in the field of alliance chain cross-chain technology:

(1)

Cross-chain Identity Authentication Framework: We propose a novel authentication scheme based on a distributed trust model that leverages the inherent trust characteristics of consortium blockchains. This eliminates security risks and performance constraints associated with third-party intermediaries, enabling direct cross-chain communication while maintaining robust security.

(2)

Cross-chain Anchor Node Architecture: We introduce the concept of cross-chain anchor nodes as a lightweight alternative to traditional cross-chain routing. This architectural design enhances data transfer efficiency while preserving the security properties of the underlying blockchain networks, particularly benefiting consortium environments with established organizational trust relationships.

(3)

Smart Contract-based Exchange Framework: We develop a comprehensive smart contract framework for cross-chain identity authentication and data exchange. This includes specialized certificate verification, data encryption, and operational logging contracts that provide end-to-end security for cross-chain interactions while significantly improving performance metrics.

The remainder of this paper is structured as follows: Section 2 reviews related work on blockchain interoperability and cross-chain technologies; Section 3 presents our distributed trust model; Section 4 describes the cross-chain interaction mechanisms; Section 5 details the implementation of our smart contract framework; Section 6 provides experimental validation and performance analysis; and Section 7 concludes with implications and future research directions.

2. Related Work

2.1. Blockchain Application Development Status

As the key technology of Web 3.0, blockchain has attracted worldwide attention and achieved considerable development. Blockchain has grown from a virtual currency represented by Bitcoin [8] to a financial application represented by Ethereum [4]. Finally, it has further expanded its scope of use to become a technical means to solve the problem of mutual trust and data transmission security in all trades and professions. Blockchain has become a strategic technology to support the development of the digital economy.

The development of digital native applications based on the public chain is very booming. Based on the fundamental applications of cryptocurrency and NonFungible Tokens (NFTs), blockchain technology has expanded to support various extended applications, including asset issuance, asset confirmation, payment, and settlement systems [9,10].

In addition, blockchain continues to expand its application in other fields, but it encounters some obstacles in commercial operation and promotion. The main reason for the problem is that the current blockchain is mainly based on public blockchain digital native applications, which have significant differences from existing network applications. Some of the problems currently existing in public blockchain limit the construction of the blockchain ecosystem [11]. For example, public chain applications based on Proof of Work (POW) consensus mechanisms have caused significant resource waste, leading to sustainability concerns in blockchain implementations. And the adoption of blockchain into the mainstream includes its widespread association with cryptocurrencies, which makes it susceptible to fraud in the minds of many [12].

As a result, although blockchain technology has demonstrated significant advantages, a single application scenario cannot achieve the vision of Web 3.0 to establish an open Internet ecosystem. The digital application of the real economy based on the consortium blockchain is the main way to solve this problem. Therefore, the blockchain has gradually formed a digital application of the real economy corresponding to the digital native application around the consortium blockchain system [13].

Although the application based on consortium blockchain sacrifices some decentralization characteristics, it is more in line with the current development direction of network applications. Consortium blockchain can integrate or supplement current network applications, such as P2P file storage and sharing [14], data integrity detection [15], cross-domain authentication [16] in the Internet of Things, and logistics traceability in the supply chain [17].

China has even proposed the concept of an open consortium blockchain platform based on consortium blockchain technology, combining public blockchain with traditional consortium blockchain, allowing a wider range of participants to join the network while retaining a certain degree of access control and privacy protection mechanisms.

2.2. Web 3.0 and Decentralized Authentication

Recent research has enhanced Web 3.0 validation by integrating blockchain, delving into diverse decentralized strategies ranging from Ethereum-based credential management to reward-based verification systems. These progressions have shown significant advancements in transaction efficiency, user confidentiality, and network efficacy, though issues with implementation and scalability still demand more exploration.

Petcu et al. [18] introduced a decentralized authentication framework that integrates Web 3.0 with Ethereum blockchain technology. Their approach uses wallet addresses and digital signatures instead of conventional username/password combinations. This system relies on MetaMask or similar Ethereum wallets for message signing and incorporates JWT tokens for session management. The method presents notable benefits such as increased privacy via anonymity, quicker logins than SMS authentication, and the removal of centralized credential storage. However, it confronts significant obstacles, including the need for specific blockchain expertise, susceptibility to phishing threats, minimal general support, and the potential for permanent account forfeiture if private keys are breached. This system is especially suitable for decentralized platforms that prioritize user anonymity, but it necessitates a thorough evaluation of the target users’ technical skills.

Nika et al. [19] proposed an innovative digital identity authentication system for Web 3.0 platforms. This groundbreaking verification technique combines three key elements: verified credentials, blockchain technologies, and zero-knowledge proofs. The introduced protocol merges decentralized identifiers (DIDs) for identity management, credential authentication via zero-knowledge, and blockchain credential storage. This method grants users control of their digital identities while ensuring security on multiple platforms. It offers several advantages such as reduced centralization, a 40% improvement in transaction speeds compared with standard blockchain authentication, enhanced privacy via selective sharing, and seamless integration with current Web 3.0 systems. However, implementing this system presents challenges, like the necessity for specialized cryptographic abilities to restrict broader applications, performance evaluations in controlled environments where actual scenarios are unavailable, and additional time lags in credential verification processes, demanding careful monitoring of time-sensitive applications. Additionally, the credential revocation system’s potential flaws call for more refined versions for future protocol applications.

Doe et al. [20] proposed an advanced incentive-driven verification system to ensure blockchain continuity in Web 3.0 and metaverse environments. Their approach combines game theory with blockchain technology to create a tiered reward system. This system integrates smart contracts with a flexible adjustment mechanism to improve incentive efficiency. The researchers developed a mathematical model that measures the benefits of network engagement. Additionally, they created an incentive framework that balances resource allocation and decentralization through algorithmic control. Their experiments demonstrated significant performance improvements.

Fan et al. [21] explore Web 3.0 authentication patterns by innovatively analyzing airdrop involvement in distributed communities. Their method merges data from airdrop participation with a qualitative evaluation of user actions, forming an analytical model to analyze authentication strategies, community participation, and trust-building processes in noncentralized settings. Leveraging machine learning algorithms, they have effectively found crucial links between authentication decisions and community participation results, demonstrating that authentication systems with both altruistic and profit-driven incentives garner 35% greater user participation rates and a 42% improvement in trust metrics over conventional single-incentive models. Yet, the study’s drawbacks are notable: emphasizing airdrop-based systems might not completely embody all the various Web 3.0 authentication cases, the sample indicates a possible selection bias owing to the unique characteristics of airdrop users, and the dependence on past data might not fully capture evolving trends in the evolving landscape of Web 3.0.

Tennakoon et al. [22] introduced the Smart Redbelly blockchain with a refined consensus method for Web 3.0 validation. This approach merges modified Byzantine Fault Tolerance protocols with advanced congestion control algorithms. The system implements three key innovations: concurrent transaction validation, adjustable block size, and dedicated layer-2 scaling. Performance improvements include 65% higher transaction processing capacity, 40% reduced congestion during peak traffic, and 30% faster validation while maintaining security standards.

The latest studies reveal the revolutionary merging of Web 3.0 with identity verification via blockchain, leading to substantial progress in decentralized frameworks. Research has demonstrated these advancements by several means, like Ethereum-driven authentication using wallet addresses, zero-knowledge proof systems, and incentive-based verification systems. Such advancements have yielded quantifiable improvements such as 40% faster processing speeds, 48–54% increased network value, and 35% greater participation in systems with altruistic and profit-oriented incentives. Nonetheless, persistent issues related to technical skill sets, security weaknesses, and scalability during peak network activities suggest a need for ongoing fine-tuning to attain widespread acceptance.

2.3. Blockchain Identity Management Solutions

Current studies show growing interest in blockchain identity management methods to build distributed confidence in IoT settings. Traditional systems use centralized control, but blockchain technology creates decentralized systems for safe and independent identity verification. These methods utilize distributed ledger technology to produce clear and unchangeable identity records, thus preventing isolated failures in IoT setups.

Sadique et al. [23] proposed a method for managing edge IoT device identities via distributed ledger technology, which allows for decentralized management and verification of device identities through intricate layers, integrating both private licensing and cloud alliance chains within the fog computing layer. This technique aids in faster response times, enhancing data confidentiality and security. Despite this, it encounters significant complexity and lacks adequate validation in actual IoT device deployment scenarios.

Riadh et al. [24] developed a method for the identity management of edge IoT devices, employing a distributed ledger (DLT) and enhanced Merkle hash tree (MMHT). This setup incorporates AES-128 encryption for strong and effective authentication, reducing processing duration by 36%, but it is not practically verifiable, even in real IoT environments.

Gupta et al. [25] suggest a distributed identity management framework merging blockchain, IPFS storage, AES encryption, and IoT technology. Key benefits include bolstered security via decentralized storage, securing biometric and demographic data with encryption, and bolstering data integrity through blockchain’s unchangeable ledger system. Yet, the article recognizes scalability constraints and emphasizes the need for more research on consensus frameworks and governing systems for effective execution.

Luong et al. [26] propose a privacy system integrating Zk-SNARK, blockchain, and cryptographic techniques like Shamir’s Secret Sharing (SSS) for private verification and monitoring harmful users. Its key advantage lies in its strong privacy safeguard, hiding users’ true identities from all, including the identity provider, allowing for selective feature and traceability exposure when needed. Yet, key limitations include the high computational requirements of Zk-SNARK operations, especially on resource-scarce devices, and the danger of collusion attacks if enough validators engage in malevolent collaboration outside the network.

Tian et al. [27] suggested a scheme for multi-copy data audits, centered on identity, aimed at thwarting malicious data dissemination via data detection and trust value assessment by group administrators. To lessen storage costs, data consolidation methods were implemented. Concurrently, blockchain technology was applied to facilitate decentralized trust management and aid in batch verification, enhancing audit efficiency. Yet, this approach necessitates the cooperation of various parties, adding complexity to system deployment and upkeep, and merging data in extensive data cases could add further computational load, an aspect of its practical application.

AlSobeh et al. [28] introduced BlockASP: a framework for an AOP-based model checking blockchain system. BlockASP represents a methodological framework that integrates aspect-oriented programming with model checking for blockchain systems verification. The approach employs a four-layer architecture to analyze dynamic blockchain behaviors through formal logic verification processes. Its primary advantages include enhanced security through decentralization, effective modularization of cross-cutting concerns, and real-time monitoring capabilities that enable comprehensive state verification. However, the framework demonstrates computational complexity comparable to traditional object-oriented methods and lacks robust empirical validation across diverse blockchain implementations, limiting conclusive evidence of its performance advantages in practical applications.

Hasan et al. [29] proposed a blockchain-based national digital identity framework for Palestine, presenting a methodologically sound approach that integrates decentralized ledger technology with identity management principles. The framework employs a four-tier architectural design—blockchain network, digital wallets, identity proofing services, and authentication mechanisms—while implementing graduated identity assurance levels (IP1–IP3) to accommodate service-specific security requirements. The system’s primary advantages include enhanced user autonomy through self-sovereign identity principles, cryptographic security protocols, modular scalability, and QR-based offline authentication capabilities that address infrastructure limitations. However, the framework exhibits notable limitations including occupation-related implementation constraints, substantial initial deployment costs (approximately 0.6% of GDP), and blockchain expertise deficiencies. While the conceptual model demonstrates theoretical robustness through qualitative assessment, it lacks empirical validation through quantitative performance metrics and systematic load testing, highlighting the necessity for future experimental studies to establish operational viability in the Palestinian context.

Recent research in blockchain-based identity management for IoT environments has developed several innovative approaches combining distributed ledger technology with advanced cryptographic techniques. While these solutions enhance security and trust through decentralized verification, they consistently face challenges in scalability and practical implementation. Success requires carefully balancing robust security features with system performance and resource constraints.

2.4. Inter-Blockchain Technology Research Status

With the advent of the Web 3.0, blockchain has begun to be applied to the fields of finance, economy, technology, and government affairs which leads to building a decentralized mutual trust platform for the whole industry, region, and even the whole network. Blockchain faces more complex business needs and will also face more complex data interconnection requests. It is necessary to have more convenient and changeable data interaction modes between different blockchain systems.

The classical methods of Inter-Blockchain Technology include WeCross, and Relays [30].

As a leader in blockchain cross-chain collaboration, WeCross has shown exceptional efficiency in numerous critical sectors. Its consistent interface specifications and message structure guarantee seamless compatibility across various blockchain networks and markedly boost the speed of cross-chain transactions via a dual-stage submission process. Its plug-in architecture enables quick entry into innovative blockchain networks, demonstrating efficient scalability. For security, WeCross offers all-encompassing support for cross-chain transactions by integrating extensive rights management, cryptographic proof, and distributed frameworks, thus guaranteeing the reliability and consistency of cross-chain activities.

The technology of Relays cross-chain facilitates comprehensive interoperability in blockchain through the creation of Relay nodes. By employing a uniform protocol transformation process, it ensures dependable blockchain communication and enhances the speed of cross-chain dealings via streamlined client validation and refined messaging methods. Relays’ architecture is structured modularly to foster adaptable entry to novel blockchain networks, highlighting its scalability. Concurrently, it utilizes a distributed Relay node network to establish an all-encompassing cryptographic validation system with precise control of permissions, thus forming a robust security framework for cross-chain activities.

With the continuous development of related research, the current cross-chain research has made continuous development. For example, Westerkamp et al. [31] proposed SmartSync. The cross-chain smart contract synchronization feature of SmartSync offers several distinct benefits: it enables smooth interaction among various blockchain networks via proxy contracts, eliminating the need to alter the original source contract code; Regarding Cross-chain Speed, by creating a state synchronization system and local execution, this system offers immediate read-access post-synchronization, thereby preventing numerous interaction lags common in conventional cross-chain methods. In terms of scalability, it integrates with multiple verification mechanisms for cross-chain (like chain Relay, notary schemes, and sharding) and demonstrates remarkable adaptability. From a security standpoint, it is built on Merkle proof and the trusted state root without depending on intermediaries, and it incorporates a transition confirmation mechanism to guarantee the integrity of state updates, culminating in a fully secured security guarantee system. Notably, the current system is capable of read-only access, which represents a compromise between security and performance.

Robinson et al. [32] introduced the Atomic Cross-chain Transactions model. This method offers distinctive benefits in numerous aspects: Its interoperability permits the separation of smart contracts across various blockchain networks via layered transaction frameworks and threshold signature processes, eliminating the necessity for intermediaries; its cross-chain Speed, thanks to the integration of synchronized blockchain and multiple proof methods, enables the verification and execution of transactions within a single block, significantly enhancing efficiency over conventional approaches, with tests revealing its capabilities of up to 39.5–65.2 TPS; and its expansibility enables it to be extended to any blockchain network with support for the same execution framework, featuring diverse consensus systems like PoW and PoS, and its router-item mode is tailored for parallel transactions. Regarding security, it develops a trust model founded on BLS threshold signatures and Merkle Proof, guarantees the authenticity and uniqueness of status updates via transformation validation, maintains security, and ensures activities through formal proof. It is important to note, however, that this approach demands considerable alterations in the foundational client of the blockchain, potentially restricting its application in certain cases.

Sober et al. [33] suggested the Decentralized Cross-blockchain Asset Transfer, demonstrating multifaceted innovative benefits: Its interoperability allows for the fragmentation of assets among various blockchains via a dual-phase burning and claiming process, employing a synchronized blockchain to oversee the state across the chain without the need for dependable middlemen. Regarding cross-chain speed and introducing systems for multi-proof and transition confirmation, a single transaction allows for verification and updates, greatly enhancing efficiency. Test outcomes indicate Protocol 1’s capability to reach 427–450 kGas processing efficiency. Its adaptability to diverse cross-chain communication modes like blockchain or Relay prophecy machines enables asset transfer, demonstrating significant versatility in security; the scheme verifies the authenticity of cross-chain data via BLS threshold and Merkle proof, ensuring its completeness through incentive methods. Concurrently, its security effectiveness is confirmed with formal evidence. Overall, this scheme’s capacity for cross-chain asset transfer ensures uniformity and decentralization, thus addressing all aspects of blockchain interoperability.

The study by Augusto et al. [34] suggests the introduction of SoK. The research indicates that existing blockchain systems for interoperability grapple with notable compromises in security, speed, and scalability. It emphasizes that in the context of security, 65.8% of the funds pilfered come from bridges in permissioned networks, highlighting critical vulnerabilities despite theoretical security benefits. In the realm of cross-chain speed, while employing methods like validity proofs and native state validation shows encouraging potential, their scalability is hindered by computational demands. Presently, the scalability of these systems is constrained, with a mere 29% of analyzed systems enabling broad data transfers between various chains. Recent methods, such as zero-knowledge proofs, may improve privacy and scalability, but they demand significant progress in generating proof efficiency and meeting trusted setup standards. The study concludes that finding a balanced solution in these aspects is still challenging, with existing ones frequently at the expense of other aspects.

The summary of the above five methods is shown in

Table 1. Comparison of Cross-Chain Solutions.

Solution	Interoperability	Cross-Chain Speed	Expansibility	Security
WeCross	Asset exchange, contract invocation	Fast (dual-stage submission)	Strong (plugin architecture)	Strong (permission management, crypto-proof)
Relays	Asset exchange and transfer	Fast (simplified validation)	Strong (modular architecture)	Strong (distributed node network)
SmartSync	Asset exchange (proxy contracts)	Relatively slow (instant read)	Relatively strong (multiple validation)	High (Merkle proof)
Atomic Cross-chain	Asset exchange (layered framework)	Slow (39.5–65.2 TPS)	Limited (client modification needed)	High (BLS threshold signature)
Decentralized Transfer	Asset exchange (dual-phase)	Medium (427–450 kGas)	Limited (multiple communication modes)	Medium (BLS and Merkle proof)
Distributed Private Key	Asset exchange and transfer	Slow	Limited	Medium (distributed key control)

.

Analyzing six cross-chain options reveals significant trends and compromises in blockchain’s interoperability realm. WeCross and Relays excel in speed and expandability, utilizing their advanced structures for effective cross-chain transactions and ensuring solid security. Conversely, SmartSync and Atomic Cross-chain Transactions emphasize security, using advanced cryptographic methods like Merkle proofs and BLS threshold signatures, though with trade-offs for reduced transaction speed. The decentralized transfer model offers a fair balance, ensuring moderate success across all metrics, whereas the distributed private key control system primarily concentrates on security via its specialized key management. This study uncovers a steady balance between security and effectiveness in cross-chain systems, underscoring the necessity for choosing solutions tailored to each use case’s unique needs and priorities. Importantly, all systems preserve fundamental interoperability characteristics for asset exchange, signifying a developed base for cross-chain dialogue, even with diverse implementation strategies.

2.5. The Development of Relays

The Relays use a partially trusted third party as an intermediate medium for inter-chain interaction. This is a more direct way. The most important role of the intermediate medium is to forward cross-chain requests [35]. The initial Relays only refer to the Relay chain mechanism derived from the Sidechains. When the main chain in the Sidechains has multiple side chains, the main chain is called a Relay chain, and the side chains interact with the main chain as an intermediate medium. The potential of the Relay chain at this stage has not been fully explored, and the application scenario is only an asset cross-chain.

With the deepening of the research on the Relays, the access problem of heterogeneous chains is solved by adjusting the structure of the Relay chain, and various types of service interfaces are provided by the Relay chain in the cross-chain process, which greatly expands the application scenarios of the cross-chain scheme. For example, Cosmos [36] designed an Inter-blockchain Communication Protocol (IBC) to interact the parallel chain with the Relay chain Cosmos Hub. By splitting the data interaction into two separate transactions between the Relay chain and the parallel chain, the cross-chain interaction between the chains is realized and the multi-level networking through the Cosmos Hub is supported.

The key to cross-chain is inter-chain communication, so the most important thing is to meet the trusted communication between the two parties. Cross-blockchain gateway came into being. This concept has been mentioned in Polkadot [37]. Its main role is to identify and forward inter-chain communication. WeCross is a simple cross-blockchain routing, which directly uses cross-blockchain routing to forward cross-chain requests. It can process cross-chain transactions and data transmission quickly and efficiently, improve the throughput and efficiency of the system, and is more in line with the characteristics of data transmission between consortium blockchains.

There are essential differences between cross-blockchain routing and Relay chain application scenarios. The scene of the Relay chain is assets transfer, acting as a trusted third party to review the security of the communication process. This is because the two participants of the asset-based data cross-chain are actually unable to trust each other and the communication data needs to be forwarded by a third party. The main scenario of the cross-blockchain gateway is the cross-chain transmission of nonasset data and the service provision of smart contracts so that the requirements for security are low. Therefore, the two methods have their advantages. In addition, there exists the hybrid Relay model, such as BitXHub [38], which combines cross-chain routing and Relay chains to meet the cross-chain requirements of the high security of assets and high efficiency of data cross-chain. BitXHub designs a protocol (Inter-Blockchain Transfer Protocol (IBTP) that connects the application blockchain and the Relay blockchain through the cross-blockchain gateway to form a cross-chain network. Figure 1 is the structure diagram of BitXHub.

With the increase in cross-chain data interaction scenarios, the huge amount of data causes performance problems in the Relay mechanism. In the traditional cross-chain scheme, the Relay chain as an intermediate medium needs to verify the transaction information of the application chain, which means that the interaction process between parallel chains actually needs to experience two interactions between parallel chains and Relay chains. Cross-blockchain routing also introduces a third party, which has certain security risks. Therefore, in the Web 3.0 era, the goal of cross-chain is not only limited to the data or assets transfer but also provides services between different blockchains, especially in the field of blockchain information platforms based on consortium blockchain. Therefore, this study designs a cross-chain scheme in the form of a direct connection to meet the needs of data cross-chain efficiency.

3. The Model of the Scheme

3.1. Distributed Trust Model of Consortium Blockchain

The proportion of the consortium blockchain in the blockchain industry has gradually increased, and open consortium blockchain platforms have become the star of China’s blockchain industry. The essential difference between the consortium blockchain and the public blockchain is that the consortium blockchain is jointly managed by various organizations, which makes consortium blockchain a basically credible network environment. This feature can be used to achieve efficient cross-chain authentications between consortium blockchains.

Although a unified root CA’s hierarchical framework offers a stable trust system within a singular federated blockchain, adapting it for multi-chain settings presents substantial theoretical and practical hurdles. Conversely, in a cross-chain context, the dispersed trust system needs to integrate several root cases, serving as the fundamental trust foundation for each blockchain network.

The ability to adjust to diverse chain scenarios is achieved through a federated trust system that establishes trust between domains. These systems implement a two-layered trust strategy: an in-chain, hierarchical trust based on standard PKI/CA systems, apt for every blockchain, and inter-chain trust developed from root CA mutual authentication in separate blockchain networks.

The CTL system aids in this growth by allowing the cross-identification of various blockchain networks’ main cases. In instances where blockchain A needs to authenticate a certificate from blockchain B, it points to blockchain B’s root CA in its list. This process forms a cross-junctional trust route over both organizational and blockchain borders, all while preserving hierarchical verification systems within each chain. Figure 2 showcases this inter-blockchain trust structure, demonstrating how numerous root cases (root CA1, root CA2, root CA2) form trust connections by mutually acknowledging them but preserving their authoritative roles in their individual fields.

The consortium blockchain is also known as the permission blockchain. It is the identity audit and verification of the nodes that want to join the chain and the identity management of the nodes is realized through the access control part between the organizations [39]. The identity in the consortium blockchain determines the exact authority of the resource and the access to the information owned by the participants in the blockchain network. Identity management is mainly realized through the Public Key Infrastructure/Certificate Authority (PKI/CA) system. For example, CAs are built in the consortium blockchain such as Hyperledger Fabric and Blockchain Open Source (BCOS) to verify identity. In the consortium blockchain, CA often appears in a cluster manner, usually using a hierarchical model. For example, there are multiple CAs in the Fabric, and each intermediate CA has a parent CA, which can eventually be associated with the Root CA through this relationship. Based on ensuring sufficient certificate processing ability, this trust model is more convenient for generating a certificate chain and building a trust path.

In addition to the hierarchical model, there is also a trust model called a Certificate Trust Lists (CTL), which is a data structure that contains a list of ’ trusted certification authorities’ after signing, including a set of trusted CA lists, which is a commonly used method to verify the credibility of other’s certificates. In the multi-chain scenario, the Root CA of each chain can be added to the trust list to form a cross-chain trust system based on the trust list, and on this basis, combined with the hierarchical trust system in the chain to achieve multi-chain trust domain integration. It not only lays the foundation for cross-chain identity authentication but also flexibly adjusts the communication structure between chains by modifying the trust list. The trust model between chains is shown in Figure 2.

After the cross-chain distributed trust model is formed, the trust transfer can be achieved among the consortium blockchains, hereby the cross-chain trusted communication can be realized. The common blockchain hierarchical structures include a data layer, network layer, consensus layer, incentive layer, contract layer, and application layer. Because this study is oriented to the consortium blockchain, the consortium blockchain will not adopt the consensus algorithm of an incentive nature such as Proof of Work (POW), there is no incentive layer. The consensus algorithm is regional, so usually the cross-chain scheme does not involve the integration of the consensus layer, and there is no design of the consensus layer in this study. This study focuses on certificate reception and cross-chain identity verification, mainly on the contract layer and application layer. The model is shown in Figure 3.

We called the chain of the request data source chain and the data located chain called the target chain in this study. Chain A is the source chain and Chain B is the target chain in this figure. The users of Chain A obtain their certificates from themselves, request cross-chain communication from Chain B, and use Chain B as the verifier for cross-chain certificate authentication. After the application layer of Chain B receives it, it is verified by the Certificate Verification Smart Contract (CVSC), and the verified certificate is stored in the Communication Certificates Trust List (CCTL). The specific process of CVSC is shown in Algorithm 1.

Certificate Certification Smart Contract (Algorithm 1) implements a comprehensive certificate validation mechanism for cross-chain authentication in consortium blockchain environments. The contract processes three essential input parameters: a root certificate in PEM format, a user certificate byte stream ($UcertBytes$), and a user identifier ($userId$). The validation process follows a systematic workflow that commences with computing a cryptographic hash of the root certificate, followed by querying the blockchain state to verify the root certificate’s existence and validity. Upon successful root certificate validation, the contract proceeds to parse the user certificate and store the validated certificate information in the blockchain’s state database using the provided user identifier. This implementation ensures robust certificate management and establishes a foundational trust layer for cross-chain operations, with comprehensive error handling mechanisms to maintain system integrity throughout the certification process.

The trusted communication certificate list is different from the trusted trust list. CTL is a predefined list of items signed by trusted entities which is a certificate hash table or file name list and does not store certificate entities. CCTL is mainly used to store and verify the passed certificate entity. It uses inert deletion and the Least Recently Used (LRU) algorithm to realize fixed-length trusted certificate data storage, which is convenient for signature verification in subsequent cross-chain requests. Both of them are stored on the blockchain, which facilitates the use of smart contracts and ensures their security.

Algorithm 1 Certificate Certification Smart Contract

Input: 1: $RcertBlock$: Root certificate PEM format byte stream 2: $UcertBytes$: User certificate byte stream 3: $userId$: User identifier Output:  Validity Verification of Certificate 4: function CertificateVerification($RcertBlock,UcertBytes,userId$) 5:     $hashValue\leftarrow hash\left(RcertBlock\right)$ 6:     $resultsIterator\leftarrow contractapi.GetQueryResult\left(hashString\right)$ 7:     if $err\ne nil$ and $!resultsIterator.HasNext\left(\right)$ then 8:         return $result($“invalid root certificate”) 9:     end if 10:   $Ucert\leftarrow ParseCerti(UcertBlock.Bytes)$ 11:   $err\leftarrow contractapi.GetStub\left(\right).PutState(userId,Ucert)$ 12:   if $err\ne nil$ then 13:        return $result($“user certificate storage failed”) 14:   end if 15:   return $result($“verification passed”) 16: end function

3.2. Cross-Chain Collaboration Architecture

Figure 4 illustrates the sophisticated cooperative framework for the suggested cross-chain validation approach. This structure includes two main blockchain areas, each with unique functional layers and interaction techniques. On Blockchain A, the Authentication Entity starts the cross-chain authentication and possesses certification rights, whereas the Root CA acts as the trust hub and issuer. Blockchain B features a tri-layer design: The Application Layer manages certificate acceptance and identity authentication mechanisms; the Contract Layer verifies certificate verification via smart agreements; and the Data Layer upholds both the Certificate Trust List (CTL) and Communication Certificate Trust List (CCTL) for solid trust administration. This tiered arrangement guarantees secure and effective cross-chain authentication, preserving the independence of separate blockchain networks.

3.3. Attack Vectors and Security Model

This research presents an extensive security framework addressing diverse risks in blockchain cross-chain consortium dealings, encompassing Sybil attacks, mitigated by methods of multi-signature entry ($m>2n/3$), setting up limited nodes, and advancing trust evaluation capabilities to fight identity trickery. It leverages weaknesses in smart contracts via modular division, the principle of least privilege, and state operation verification for contract safety assurance; risks to data accuracy, creation of certificate chains and comprehensive encryption, and in-depth audit records; and changes in trust models, prevented by confirming certificate authority clusters and hierarchical certificate validation to safeguard against trust list tampering.

This study develops a distributed trust model centered on identity authentication, incorporating fundamental security mechanisms, such as a cross-organizational trustworthy system that melds hierarchical certificate authority (CA) systems with Certificate Trust Lists (CTLs); a unique smart contract architecture that includes a variety of certificate verification contracts (CVSC), signature verification contracts (SVSC), data encryption contracts (DESC), and operation recording contracts (ORSC), as well as mechanisms for channel isolation to safeguard data confidentiality across various organizations, prioritizing identity verification through certificate chain validation over conventional consensus methods and an array of smart contract safeguards that blend re-entrancy attack prevention with state consistency verification and rigid access checks.

4. Cross-Chain Interaction and Data Flow Mechanisms

The proposed cross-chain interaction and data flow mechanism implements a comprehensive control framework that ensures secure and efficient data transmission between consortium blockchains. This mechanism integrates data validation, flow authentication, and destination verification into a unified process, providing robust security guarantees while maintaining system performance. The control logic validates the data source authenticity, authenticates the entire flow process, and verifies the destination chain’s legitimacy, forming a complete chain of trust for cross-chain operations.

To enhance this system, there are three distinct smart contracts that collaborate in managing various elements of inter-chain interactions. The Certificate Verification Smart Contract (CVSC) facilitates identity verification via a PKI-dependent system, guaranteeing the correct authentication of participating parties prior to their cross-chain actions. Data Encryption Smart Contract (DESC) ensures safe data exchange between chains, adopting robust cryptographic methods for data preservation and privacy in transit. Operation Record Smart Contract (ORSC) upholds an extensive audit history for all cross-chain transactions, ensuring complete tracking and responsibility of these operations.

This unified method successfully tackles major issues in cross-chain communications such as building trust, safeguarding data, and tracking operations. It merges strict control systems with tailor-made smart contracts to offer a protective and effective system for cross-chain data exchange, ensuring the independence and safety standards of consortium blockchain settings.

This approach shows major benefits over conventional cross-chain methods, especially in cutting down on third-party reliance and security hazards. Performance assessments reveal greater effectiveness in cross-chain activities, evidenced by lower delays and higher throughput than standard Relay-driven methods. Consortium blockchains leverage this method to secure proficient cross-chain communication while preserving their natural security attributes and operational autonomy.

5. Cross-Chain Interaction Scheme Based on Smart Contract

5.1. Cross-Chain Communication Scheme

An essential structure is required for the cross-chain communication system to supervise smart contract interactions among different chains. The CB-SCL (Cross-chain Smart Contract List) embraces a comprehensive data structure with three fundamental components. The essential contract information, embedded in the metadata of smart contracts, consists of vital contract details such as addresses, version control systems, chain identifiers, and deployment durations. Additional assets like access control parameters, controlling inter-chain interactions, are incorporated. The functional specifications segment comprises comprehensive API documentation, input–output parameter frameworks, and operational protocols that bridge various chains, ensuring consistent interaction patterns and the organizational control zone defines access permissions for cross-chain, tailored policies for each channel, and requirements for audit trails, ensuring the network’s operational dependability.

In the blockchain, the data on the chain is operated by smart contracts, so data cross-chain often needs calling smart contracts across the chain. The cross-chain interaction scheme is designed based on the cross-chain authentication method. After successful cross-chain authentication, the smart contract is called to operate cross-chain data, then the results are encrypted and returned.

In the process of cross-chain interaction, the processing of data is handed over to the smart contract, and the call to the smart contract needs to know the specific contract address and related data. Before the cross-chain smart contract is invoked, the shared control of the publicly available smart contract and its related data is carried out by the data chain itself. After invoking the smart contract across the chain, the operator and the specific operation content of the stored data realize the comprehensive traceability of the data operation.

The cross-chain interaction is secured through multiple layers of smart contract security controls. These include re-entrancy protection, strict access control, and comprehensive input validation, ensuring the integrity and safety of cross-chain operations while maintaining system efficiency.

Before initiating a cross-chain request, the data requester should know the requested data and the corresponding contract address. Therefore, a Cross-chain Smart Contract List (CB-SCL) should be maintained in the cross-chain organization. The data in the list should include the address of the smart contract, the functional description of the contract, the description of the relevant data, the channel, and the parameters attached instructions. This list can also ensure that the source chain can obtain the latest accessing interface in time. After the cross-chain calling smart contract is completed, the smart contract is used to store the requester’s signature, request information, and return results in the channel to which the contract belongs and the identity information in the identity authentication process will also be retained. The organization in the same channel accesses the request data according to the endorsement strategy of the channel to achieve access control of cross-chain operations. The interaction process of each layer in Chain B is shown in Figure 5.

Chain B as the receiver of the request calls the smart contract through the application layer to operate cross-chain requests. There are four operations in the contract layer in the Figure Contract execution refers to the invocation of the contract in the cross-chain request. The invoked contract does not hold a clear direction and does not depend on certain data. The cross-chain request only calls the contract execution algorithm. In addition, Chain B also needs to run signature verification, data result encryption, and operation records at the contract layer, which are Signature Verification Smart Contract (SVSC), Data Encryption Smart Contract (DESC), and Operation Record Smart Contract (ORSC).

The CB-SCL operates through three methodically designed layers. This structure ensures effective contract administration and secure implementation. Initially, the registering interface introduces a unique protocol for registering new smart contracts, necessitating verification by multiple parties from entities and ensuring automatic version control and compatibility affirmation. The intermediary access control tier governs access rights for organizations via channel-dependent endorsement tactics, verifying smart contract requests against pre-established organizational authorizations. The execution tier orchestrates contract activities across various chains, guaranteeing adherence to consensus regulations while preserving extensive transaction logs within each organizational pathway.

5.1.1. Signature Verification Smart Contract

SVSC is responsible for the signature verification. It is necessary to obtain the list of trusted communication certificates on the chain to perform the signature verification algorithm through the certificate information. If the verification is not successful, the message will be directly returned. The data requester first operates cross-chain certificate authentication and then requests data across the chain. The specific process is shown in Algorithm 2.

Algorithm 2 Signature Verification Smart Contract

Input:  request metadata ciphertext:m, signature pair: r&s, user identifier: userId Output:  Signature Verification 1: cert, err:= contractapi.GetState(userId) 2: if err != nil then 3:     //if the certificate is not found 4:     return result(“the certificate has expired, re-certify”) 5: end if 6: PK = cert.PubKey //get the user’s public key from the certificate 7: result = ecdsa.Verify(PK, r, s) //signature verification 8: return result //return the verification result

The Signature Verification Smart Contract (Algorithm 2) extends the security framework by implementing cryptographic signature validation for cross-chain communications. The contract operates on three critical inputs: request metadata (m), signature components ($r\&s$), and a user identifier ($userId$). It initiates the verification process by retrieving the previously stored certificate from the blockchain state, incorporating certificate expiration verification as an integral security measure. The core functionality leverages the ECDSA (Elliptic Curve Digital Signature Algorithm) for cryptographic validation, utilizing the public key extracted from the retrieved certificate to verify the signature’s authenticity against the provided data. This implementation ensures the integrity and authenticity of cross-chain communications while maintaining atomic operation consistency throughout the verification process, thereby establishing a secure foundation for trusted cross-chain interactions in consortium blockchain networks.

Signature verification is used in the contract using an ECDSA-based verification algorithm. The parameter set has been obtained during the process of parsing the certificate and can also be requested from the user’s root CA. After the signature verification is passed, the information of the contract and the parameters of the calling contract are written to the request, so the smart contract can be called by parsing the request information. As the smart contract runs automatically, the execution result of the contract is accurate, and the application layer is carried on the node provided by Chain A, so the correctness of the execution result of the contract can be guaranteed.

5.1.2. Data Encryption Smart Contract

After the execution of the contract, DESC encrypts the data using the requester’s public key encryption. Similar to SVSC, DESC also needs to use the trusted communication certificate list on the chain to store the certificate information so that it can execute the encryption algorithm. The specific DESC process is shown in Algorithm 3.

Algorithm 3 Data Encryption Smart Contract

Input:  Contract Execution Result Plaintext: m, user identifier: userId Output:  Plaintext Pair 1:   cert, err = contractapi.GetState(userId) 2:   if err != nil then 3:       // if the certificate is not found 4:       return result(“the certificate has expired, re-certify”) 5:       return result(“the certificate resolution has failed”) 6:   end if 7:   hashText = sha256(plainText) 8:   PK = cert.Pub //get the user’s public key 9:   result = Encrypt(Reader, PK, m) //encryption 10: return result //return the ciphertext

Algorithm 3 implements a cryptographic framework for secure cross-chain data transmission within consortium blockchain architectures. This smart contract performs a systematic sequence of certificate validation, cryptographic processing, and secure transmission operations. The implementation incorporates multiple security layers: certificate-based authentication for establishing cryptographic foundations, expiration verification to prevent deprecated credential usage, SHA-256 hash generation for maintaining data integrity, and asymmetric encryption using recipient public keys extracted from validated certificates. This security-by-design approach effectively ensures that only intended recipients with corresponding private keys can decrypt transmitted data, thus providing a computationally efficient yet robust security foundation for cross-chain data exchange in distributed trust environments.

The data encryption uses the ECC algorithm. The parameter set is obtained in the process of parsing the certificate and can also be requested from the user’s root CA.

5.1.3. Operation Record Smart Contract

One of the characteristics of blockchain is traceability, which can not only query historical data but also trace the historical operators of data. In cross-chain interaction, operating data only through smart contracts will cause a failure to track cross-chain data operators. Therefore, after the cross-chain calls the smart contract, it is necessary to store the data operator and the operation content to achieve all-around data traceability. After the smart contract is executed, Chain B calls ORSC to store the requester’s signature, request information, and return results, while retaining the identity authentication information at the same time. The organization in the channel accesses the requested data according to the endorsement strategy to achieve access control for cross-chain operations. ORSC stores results, requests, and identity information, and the encryption contract invoked results back to the requester. The ORSC contract is mounted on the anchor node and the access rights of the cross-chain operation record are limited to its channel, which ensures that the organization in different channels cannot detect the operation record. The cross-chain operation record is stored in the current channel, due to the characteristics of data isolation among channels, other chains cannot obtain the cross-chain operation data in the own channel, so the privacy of the cross-chain operation is guaranteed.

5.1.4. Smart Contract Execution Optimization

The research suggests an all-encompassing framework for optimizing smart contract execution that effectively manages the efficiency of contract execution in cross-chain situations. The framework, built on the current tri-level smart contract framework (CVSC, DESC, ORSC), enhances the system’s security and dependability by intensifying the process of contract implementation and deepening its efficiency. In Certificate Verification Smart Contracts (CVSC), the framework streamlines the verification procedure by thoroughly integrating it with the CCTL system. It employs CCTL and LRU, a fixed-length storage solution, to significantly diminish the frequency of verification and greatly advance certificate verification procedures. When it comes to Data Encryption Smart Contracts (DESCs), they enhance encryption strategies and processing processes, thereby ensuring data security and efficiency. This optimization plays a crucial role in transferring information across multiple-chain trust domains, directly influencing the system’s throughput and delay. At the operational record smart contract (ORSC) stage, an effective audit trail is attained by refining the blockchain status update process, guaranteeing full traceability in cross-chain activities while preserving high-chain performance in simultaneous scenarios.

5.1.5. Cross-Chain Component Specifications

The suggested inter-chain architecture introduces an advanced, multi-part structure greatly improving the reliability and effectiveness of inter-blockchain communication. The CVSC, a pivotal component of the trust verification process, integrates sophisticated protocols for parameter validation and refined algorithms for chain validation of certificates. Its incorporation features an intelligent caching layer for authenticated certificates, markedly cutting down computational expenses while upholding strict security protocols.

The innovative design of cross-chain anchor nodes is noteworthy, featuring a weighted round-robin algorithm for load balancing along with constant health observation. They sustain dynamically proportioned connection pools and execute a priority-driven request queue control, optimizing the usage of resources and ensuring system robustness under differing load scenarios. The systems’ failure detection and recovery systems ensure strong consistency and operational effectiveness.

5.2. Cross-Chain Model Based on Cross-Chain Anchor Nodes

5.2.1. Multi-Level Certificate Management System

In order to deal with the computational overhead in large-scale cross-chain authentication scenarios, an enhanced certificate management system is proposed in this paper. The system uses an innovative CCTL framework to optimize the certificate management process by combining dynamic caching and efficient storage methods. In terms of architecture design, the system implements a composite storage structure, which combines high-speed memory cache with blockchain persistent storage to deal with frequently accessed certificate data and low active certificate data, respectively. This architecture not only ensures fast access to commonly used certificates but also guarantees a complete audit record through blockchain storage. In order to further improve the processing efficiency, batch processing technology is introduced to support parallel signature verification and authentication task processing. At the level of network transmission, the system adopts advanced certificate compression technology, including selective field transmission and dynamic compression ratio adjustment based on network conditions, which effectively reduces the network load. Experimental data show that the management system can significantly reduce authentication latency in typical cross-chain scenarios while maintaining complete record accuracy. By introducing these optimization mechanisms, the system significantly improves the efficiency and scalability of certificate management while maintaining high security, and provides strong technical support for large-scale cross-chain interaction.

This architecture enhances the foundational distributed trust model and addresses the performance constraints in cross-chain verification via technological advancements. The experiment indicates the system’s efficacy in managing substantial concurrent requests and offers a dependable technical route for establishing a proficient alliance chain cross-chain system.

5.2.2. Cross-Chain Model Implementation

Before discussing the specific implementation of cross-chain anchor nodes, it is essential to understand how cross-chain organizations maintain and utilize the CB-SCL through a sophisticated distributed consensus mechanism. Each participating organization contributes to multiple critical processes, actively engaging in validating new contract registrations, maintaining contract metadata integrity, and enforcing access control policies within their respective channels. This collaborative framework enables participating organizations to maintain synchronized copies of the CB-SCL while participating in periodic audits of contract operations. The CB-SCL thus serves as a critical bridge between organizational boundaries, facilitating secure and controlled cross-chain interactions while preserving the autonomy of individual chains.

The cross-chain communication scheme is the core content of the cross-chain interaction scheme. In the specific implementation process, in order to eliminate the security risks brought by third parties, this study proposes a cross-chain model based on cross-chain anchor nodes. The difference between cross-chain anchor nodes and ordinary nodes is that cross-chain anchor nodes need application layer services dedicated to cross-chain. The organization with cross-chain anchor nodes is called a cross-chain organization. There is at least one cross-chain anchor node in the cross-chain organization, and the load balancing server is used to assign cross-chain requests to each anchor node to improve the availability of the system. As a basic member of the channel, the organization can flexibly set the cross-chain access rights of the data using the endorsement strategy within the channel. In addition, the contract calling result is returned by the cross-chain anchor node, and the cross-chain access control is realized by combining the access strategy of the channel.

A cross-chain is an off-chain service component, which has little impact on the underlying structure of the blockchain. Because the organizational structure of the distributed trust model based on the trust list is relatively loose, the main interaction among chains is implemented on the application layer of the blockchain. The cross-chain model is shown in Figure 6.

In the process of establishing cross-chain communication, Certificate Trust List (CTL) and Routing Address List (RAL) can be maintained through sharing, and cross-chain requests for CTL and RAL can be achieved without authentication. Therefore, as long as the trusted cross-chain organization routing is obtained, the chain CTL can be requested to supplement and maintain its own CTL to achieve trust transfer.

By adding cross-chain anchor nodes to the chain and updating the open nodes and CTLs outside the chain, cross-chain communication can be achieved with other chains. It truly achieves a lightweight and pluggable efficient consortium blockchain cross-chain scheme without a third party. In addition, because the scheme of this study mainly uses smart contracts and application layer services, this scheme can meet the cross-chain requirements between various heterogeneous consortium blockchains.

The CB-SCL’s technical deployment utilizes an advanced data structure framework aimed at enhancing contract management and access control checks. Its primary structure revolves around a ContractMetadata framework, which incorporates crucial operational elements. This framework upholds key data fields, including an address identifier for accurate contract positioning, a chain identifier represented as a 32-byte value for distinct chain identification, and a timestamp for version control and timing tracking. This system includes a dynamic authorization mapping mechanism, correlating organizational addresses to boolean access permissions, thus offering detailed control over inter-chain communication. Moreover, it preserves a range of supported procedures represented as 32-byte values, aiding in thorough operation monitoring and validation.

Implementation of the contract registry system involves a mapping framework, linking distinct identifiers with each ContractMetadata instance. This architecture facilitates effective contract retrieval processes while maintaining robust access control verification systems. The registry system streamlines cross-chain operations by fine-tuning data access patterns and organized metadata management protocols, allowing the CB-SCL to handle the intricacies of cross-chain interactions efficiently, all the while adhering to stringent security and autonomy standards.

The architectural design of this system guarantees operational effectiveness and security throughout the network, establishing a solid base for inter-chain interaction and managing contracts. It shows a focus on scalability and security needs, ensuring the adaptability required for various cross-chain situations.

5.3. Mechanism to Prevent Sybil Attacks

In order to better address the security issues of Sybil attacks, we propose solutions to the problem in this subsection.

The segment delineates a multi-layered authorization and reliability evaluation system, established at the core of consortium blockchain rights, aimed at preventing malicious nodes from creating various identities for executing Sybil attacks in inter-chain communications. It integrates organizational entry control, validation of anchor node qualifications, and dynamic trust evaluation to establish a comprehensive defense structure.

To regulate member access to an entity, rigorous entry procedures are applied in the consortium’s blockchain system. An entity, $Or{g}_i$, must obtain multiple signature validations from existing collectives before joining. With a total of n organizations, entry into new entities demands a baseline of m signatures (assuming $m>2n/3$), as shown in Equation:

$$Admission\left(Or{g}_i\right)=\left\{\begin{array}{cc}True,\hfill & \mathrm{if}\sum _{j=1}^{n}Sig{n}_j\ge m\hfill \\ False,\hfill & \mathrm{otherwise}\hfill \end{array}\right.$$

(1)

where $MaxNodes$ is the maximum number of anchor nodes allowed per organization.

Ultimately, a flexible trust assessment method has been set up for anchor nodes: For each node labeled k, its trust metric $T_k$ is computed using the formula

$$T_k=\alpha ·UpTim{e}_k+\beta ·ResponseRat{e}_k+\gamma ·SuccessRat{e}_k$$

(2)

where $UpTim{e}_k$ represents the node’s modified online duration, $ResponseRat{e}_k$ the standardized response rate, $SuccessRat{e}_k$ the node’s transaction success rate, $\alpha$, $\beta$, $\gamma$ the weight coefficients, and the total of $\alpha +\beta +\gamma$ equals 1.

The update strategy of trust score adopts a dual-track system: (1) Periodic update based on time, triggering the whole network credit reassessment with a fixed block interval (for example, after every 1000 blocks are generated). (2) Event-based triggered update, when there is an obvious anomaly in node behavior (such as continuous failed transactions exceeding the preset threshold), the trust re-calculation is performed immediately. To prevent malicious nodes from manipulating the trust score, all trust updates must be verified by multi-organization consensus, requiring at least m organizations to sign for confirmation (where $m>2n/3$, n is the total number of organizations), thus ensuring the fairness of the scoring process.

The node’s cross-chain service qualification is determined by its trust score according to Equation:

$$Status\left(Nod{e}_k\right)=\left\{\begin{array}{cc}Active,\hfill & \mathrm{if}{T}_k\ge T_{threshold}\hfill \\ Suspended,\hfill & \mathrm{if}{T}_k<T_{threshold}\hfill \end{array}\right.$$

(3)

When a new node joins the alliance chain network, the system adopts the progressive trust establishment mechanism, initially puts the node in the trial state with limited permissions, and assigns the initial trust value of the lowest acceptable threshold $T_{threshold}$. The access process requires the new node to provide an identity certificate signed and endorsed by at least kof existing high-trust nodes (meeting the condition of $k\ge n/2+1$), and then the system performs a complete certificate chain verification on the certificate to ensure its consistency with the existing CTL. The new node gradually accumulates trust value through continuous and stable cross-chain service and can obtain formal node qualification only after maintaining good performance for successive mevaluation cycles. In terms of node exit management, the system supports two modes: In the normal exit process, the exiting node actively initiates the certificate revocation request, and the certificate revocation notice is broadcast on the whole network after the network consensus is confirmed. When the node trust score continuously drops below the threshold of $T_{min}$ or malicious behaviors occur, the system triggers a forced protocol exit. Regardless of the exit method, the updated CTL and Communication Certificates Trust List (CCTL) will be synchronized to all participating chains, and the complete behavior history of the exiting node will be retained on the blockchain for subsequent audit and security analysis. Node states based on trust scores are defined as three levels: Active ($T_k\ge T_{threshold}$), Probation ($T_{min}\le T_k<T_{threshold}$), and Suspended ($T_k<T_{min}$). Nodes in different statuses have different configurations of cross-chain permissions: only the Active node can perform all cross-chain operations, the Probation node is limited to low-risk cross-chain read operations, and the Suspended node suspends all cross-chain services. This complete node lifecycle management framework and dynamic trust evaluation mechanism complement each other, and together constitute the infrastructure of the distributed trust model in this paper, providing reliable security for the alliance blockchain cross-chain identity authentication system.

Leveraging the consortium blockchain’s sanctioned status, this framework implements measures at the organizational level and integrates a trust evaluation system for ongoing monitoring at the nodes. The system’s seamless integration of static authorization control with dynamic trust assessment successfully averts Sybil attacks while minimally hindering standard cross-chain activities. Its layered defense approach guarantees that despite an attacker registering numerous identities, sustained good behavior over an extended time is essential for earning system trust, thereby greatly raising the expense and complexity of initiating Sybil attacks.

Additionally, incorporating trust evaluation results into the cross-chain validation process detailed in Section 2.4 enhances the system’s overall security and is consistent with the distributed trust paradigm proposed in this study, thereby setting a sturdy security groundwork for future cross-chain data exchanges.

6. Program Analysis

6.1. Security Analysis

In this study, the security of the proposed cross-chain interaction scheme is analyzed and evaluated comprehensively and systematically. The analysis process mainly focuses on the two core dimensions of smart contract vulnerability and the integrity of the distributed trust model, as well as covering several key security factors in the implementation of an alliance chain.

6.1.1. The Analysis of Attacks Defense

This section provides a detailed security analysis of the scheme for Sybil attacks prevention, protection against vulnerabilities in smart contracts, data integrity, and data transmission reliability.

The Sybil attack prevention framework demonstrates methodological sophistication through its hierarchical defense architecture that integrates organizational consensus mechanisms with dynamic trust evaluation protocols. The multi-signature admission framework necessitates two-thirds majority approval from existing organizational members, thereby establishing a significant barrier against identity falsification attempts. Vulnerability surface restriction is further accomplished through an anchor node deployment limitation protocol that constrains the maximum node allocation per organization. The framework’s dynamic trust evaluation system—which quantitatively assesses node performance through operational metrics including uptime ratios, response efficiency, and transaction success rates—introduces temporal complexity that renders the maintenance of multiple high-trust identities computationally prohibitive. This integrated methodological approach effectively elevates attack cost parameters while preserving system operational efficiency, thereby ensuring security integrity provided that organizational honesty is maintained among the majority of participants.

The suggested cross-chain design creates solid protection against vulnerabilities in smart contracts by utilizing a layered hazard reduction system. It particularly uses modular contract division, in which the Certificate Verification Smart Contract (CVSC), Signature Verification Smart Contract (SVSC), and Operation Record Smart Contract (ORSC) are situated in distinct operational areas, effectively curbing the spread of vulnerabilities throughout the system’s framework. This segregation method applies the minimal privilege principle, confining each contract’s functional range to set functional parameters. Furthermore, the framework incorporates definitive execution routes fortified by cryptographic authentication procedures, thereby effectively reducing typical vulnerability risks such as re-entrancy incursions, integer overflow situations, and timestamp interference. Establishing all-encompassing thorough accounting systems via unchangeable ledger entries reinforces transactional linearity verification, averting state manipulation attacks that could otherwise endanger cross-chain data integrity. This method of dividing and enforcing susceptibility ensures the system’s robustness in protecting against possible smart contract exploitation situations through this method.

Within the data integrity assurance system, a tiered safeguarding system incorporates cryptographic verification methods and widespread consensus validation. Central to this system is the use of Certificate Verification Smart Contracts (CVSC) for consistent hash-based validation, and Data Encryption Smart Contracts (DESC) for creating secure transmission pathways with ECDSA-secp256k1 cryptographic indications. Such a principal security measure is fortified by a Byzantine, fault-resistant consensus protocol necessitating validation across multiple parties within anchor nodes, augmented by Operation Record Smart Contracts (ORSC) for unalterable audit histories. The trial validation proves the system’s effectiveness, securing no integrity breaches in 5000 tests, while keeping the system’s data transfer rate at 58 TPS for reading activities, thus laying a solid groundwork for protected inter-chain data sharing in group blockchain settings.

Cross-chain data transmission’s reliability is fortified by a complex, multi-level protection system based on cryptographic methods and decentralized trust networks. The Certificate Verification Smart Contract’s (CVSC) deployment lays a solid groundwork in cryptography for data reliability via deterministic verification processes. Moreover, the implementation of a Signature Verification Smart Contract (SVSC) alongside a Data Encryption Smart Contract (DESC) guarantees the maintenance of data integrity and secrecy during the entire transmission process. Additionally, the Operation Record Smart Contract (ORSC) ensures total imperviousness by keeping confirmable operational logs in decentralized record systems, thus maintaining data integrity through cryptographically protected audit trails. This holistic method for data integrity safety shows tangible benefits compared with standard Relay-driven methods, as shown by its excellent performance in decreasing delay and boosting throughput in controlled experimental scenarios.

To sum up, our proposed scheme can effectively solve important security problems.

6.1.2. The Analysis of Regulatory Compliance Issues

This study systematically analyzes the compliance issues of cross-chain identity authentication and data transfer in practical applications, with a particular focus on GDPR and banking regulatory requirements. Research has shown that in order to meet regulatory compliance requirements, cross-chain systems need to implement comprehensive data protection mechanisms and security controls.

In terms of data protection and privacy, the system complies with GDPR requirements by implementing multiple layers of protection mechanisms. The application of smart contract technology ensures the realization of the principle of data minimization, and the purpose of data processing is clearly defined by strictly controlling the scope of cross-chain data transmission. The introduction of the trust list further standardizes the rights of data use and effectively protects the rights of data subjects through the certificate revocation mechanism.

The system’s access control and authorization mechanisms are specifically optimized for banking regulatory requirements. The hierarchical certificate management based on PKI/CA system ensures the reliability of authentication, and the application of smart contracts realizes the fine-grained permission management. By utilizing the immutable characteristics of blockchain, the system has established a complete operational audit trail mechanism to meet regulatory compliance requirements.

In terms of data transmission security, the system has implemented comprehensive protection measures for cross-border data transmission. End-to-end encryption is achieved through encrypted smart contracts to ensure the security of data transmission. The application of channel isolation technology ensures that the data storage meets the regional requirements, and establishes a perfect cross-chain data transmission compliance verification mechanism.

In order to meet the requirements of regulatory review, a comprehensive audit support framework is designed. Operation record smart contracts achieve a complete record of all cross-chain interactions, real-time monitoring mechanisms support continuous supervision by regulators, and the system can automatically generate standardized compliance reports to meet various regulatory review needs.

This complete compliance framework achieves comprehensive coverage of regulatory requirements through technical means, ensuring that the cross-chain interaction process complies with various regulatory norms while ensuring system efficiency. The results show that reasonable system design and technical implementation can effectively balance the requirements of regulatory compliance and system performance, and provide a reliable theoretical basis for the practical application of cross-chain systems.

6.1.3. Empirical Security Analysis

To rigorously assess the security properties of our distributed trust model and cross-chain anchor nodes, we developed a systematic attack simulation framework. The experimental environment utilized Docker-based containerization (ver. 20.10.17) to simulate isolated blockchain networks while maintaining controlled network conditions. All attack scenarios were executed on identical hardware configurations to ensure reproducibility and comparative validity of results.

The simulation framework incorporates four primary attack vectors specifically targeting the proposed architecture:

Sybil Attack Resistance Testing: We implemented progressive network compromise scenarios where adversaries controlled varying proportions of network nodes (25%, 33%, and 49%). The 49% threshold was selected as a critical evaluation point, as it approaches the theoretical security boundary of our Byzantine fault tolerance implementation.

Smart Contract Vulnerability Exploitation: Systematic attempts to compromise each component of our smart contract architecture were conducted, focusing particularly on the Certificate Verification Smart Contract (CVSC), Signature Verification Smart Contract (SVSC), Data Encryption Smart Contract (DESC), and Operation Record Smart Contract (ORSC). These attempts included re-entrancy attacks, access control manipulation, and state inconsistency exploitation.

Trust Model Subversion: Attacks targeting the manipulation of the Certificate Trust List (CTL) and Communication Certificate Trust List (CCTL) were simulated to evaluate the resilience of the distributed trust architecture against trust poisoning and certificate forgery attempts.

Cross-Chain Communication Attacks: Cross-chain request forgery, replay attacks, and man-in-the-middle interceptions were systematically executed to evaluate the transaction integrity and authentication mechanisms.

The effectiveness of security mechanisms was evaluated using a comprehensive set of quantitative metrics.

As evidenced in

Table 2. Quantitative Security Metrics for Cross-Chain Authentication.

Metric	Definition	WeCross	Proposed Approach
Attack Detection Time (ms)	Average time to detect malicious activity	213.6	87.4
Attack Resource Cost	Computational resources required for successful attack (normalized CPU-hours)	42.8	76.3
System Recovery Time (s)	Time required to restore normal operations after attack detection	18.6	7.2
Transaction Integrity	Percentage of legitimate transactions processed during attack conditions	81.3%	94.7%
Trust Degradation	Decrease in system trust score after sustained attack (scale 0–100)	38.4	14.2

, our proposed approach demonstrated superior performance across all security metrics compared with the WeCross reference implementation. Of particular significance is the 58.9% reduction in attack detection time and the 13.4% improvement in transaction integrity during active attack conditions. These results empirically validate the theoretical security advantages of our distributed trust model and smart contract architecture.

6.2. Scalability and Efficiency Analysis

To guarantee the expandability and effectiveness of diverse blockchain exchanges, this research utilizes a novel framework utilizing cross-chain anchor nodes, leading to high efficiency in trans-chain interaction through the incorporation of cross-chain identity verification and dispersed trust systems.

From a theoretical standpoint, this research initially develops a dispersed trust system relying on a Certificate Trust List (CTL). This framework achieves integration of cross-chain trust domains via a hierarchical structure of certificate authorities. Integrating the root certificate into this trust list establishes a cross-chain trust framework grounded in the trust list. This system, integrated with the hierarchical trust system of the same chain, achieves the amalgamation of multiple-chain trust domains. The design of this trust model establishes a theoretical base for effective interaction among varied chains.

Regarding technological deployment, this research developed an exhaustive smart contract framework encompassing certificate verification (CVSC), data encryption (DESC), and operation record (ORSC) smart contracts. These agreements facilitate uniformity and productivity in data handling among diverse chains via uniform interface architecture. Concurrently, the cross-chain anchor node supersedes the conventional cross-link method, mitigating external risks via the Relay system and enhancing cross-chain communication efficacy.

Regarding its architectural structure, this study utilizes a channel isolation approach, facilitating dynamic distribution and simultaneous handling of cross-chain inquiries via cross-chain organization, configuring various anchor nodes, and integrating load balancing servers. The design aims to not only achieve system scalability but also facilitate adaptable access control through the channel’s endorsement policy.

As suggested in this study, employing a layered integrated approach aims to lessen computational expenses and the network overload linked to authentication and smart contract implementation in inter-chain exchanges. The distributed trust model incorporates various chains’ core cases into the shared trust roster via Certificate Trust List (CTL), leading to the development of a unified cross-chain trust system for uninterrupted trust transmission post single authentication. To this end, a Communication Certificate Trust List (CCTL) is suggested, utilizing fixed-length storage and an LRU algorithm for storing authenticated certificates, thus diminishing the likelihood of redundant authentication. The paper innovatively adopts cross-chain anchor nodes for substituting conventional cross-link pathways, thereby reducing security hazards and computational burdens associated with third-party Relay methods, and providing load balancing servers to allocate cross-chain requests for direct and effective inter-chain communication. The smart contract architecture is designed with a stratified design that separates the Signature Verification Smart Contract (SVSC), Data Encryption Smart Contract (DESC), and operation recording smart contract (ORSC), ensuring smooth signature confirmation, cross-chain data security, and extensive record-chain data security.

Additionally, we present an innovative multi-level certificate management system designed to tackle computational hurdles in extensive cross-chain authentication situations. This system features an enhanced CCTL framework, merging dynamic caching seamlessly with effective storage methods. Its heart lies in an intricate two-level storage framework, merging rapid memory caching for commonly used certificates with blockchain’s continuous storage for minimally active ones. This combined method markedly diminishes authentication delay in typical cross-chains yet preserves complete record accuracy. Its deployment elevates data processing capacity by introducing novel batch processing technologies, allowing for simultaneous signature verification and the parallel processing of separate authentication tasks. Sophisticated certificate compression approaches are utilized in optimizing network transmission, including specific field transmission and dynamic compression ratio alterations in response to real-time network scenarios.

Theoretical examination reveals that this system’s scalability and efficacy are attainable, safeguarding inter-diverse blockchain interactions by employing a distributed trust model, smart contract framework, and a cross-chain anchor node model in its entirety. The design thoroughly takes into account the structural features of the alliance chain, harmonizing cross-chain technology with the dynamics of data element movement.

6.3. Experimental Configuration

The study scheme is based on Hyperledger Fabric and Financial Services Consortium Blockchain Open Source (FISCO BCOS) to create two consortium blockchains for experiments, interact through manual application layer interface calls, and simulate the data cross-chain between consortium blockchains. The hardware and software configuration of the experimental environment is shown in

Table 3. Data Cross-Chain Experimental Environment Configuration Based on Distributed Trust Model.

Term	Parameter
Operating System	Ubuntu 18.04 LTS
CPU	Intel® CoreTM i7-11700 @ 2.50 GHz
Memory	32 GB
Hyperledger Fabric	2.2
Docker	20.10.17
Hash Algorithm	SHA256
Elliptic Curve	secp256k1
Consensus Algorithm	Raft
Block Generation Strategy	2 s/4 M/500 T

.

The block generation strategy stipulates the rules of block generation. When the number of transactions does not exceed 500 and the total data size of the transaction does not reach 4 M, the block is generated every 2 s. Under this rule, when the amount of write operation requests or the amount of data is small, the block generation of the blockchain is at a fixed time, which will make a great impact on the requests sent per unit time, which is not convenient for experimental comparison. Therefore, in the experimental process, it is necessary to reduce the impact of the block generation strategy on the experimental results as much as possible and select the appropriate request amount interval and concurrency granularity.

The Fabric network and BCOS network of this experiment are built on a host each, simulated by docker, and linked by LAN. There is only one channel in the organizational structure of the Fabric chain. The channel contains an Orderer organization, a cross-chain organization, and two ordinary organizations, and each organization node is equipped with four nodes and an intermediate CA. The entire chain only has a root CA.

Cross-chain interaction is the interaction between two systems, so the performance of the cross-chain scheme also depends on the performance and organizational structure of the blockchain itself. The smart contract of Fabric is attached to the node, and to reduce the impact of the blockchain node itself on the experimental results, it is necessary to use the single-node performance test of Fabric under the experimental environment. Hyperledger Caliper is used to test the single-node performance of Fabric.

Verification of the suggested cross-chain models uses a dual-network framework with Hyperledger Fabric v2.2 and FISCO BCOS platforms. This version is made up of a single ordering service node with a Raft agreement and four nodes in each organization. It incorporates certificate-based identity management and policies for multi-organizational endorsements, necessitating bidirectional validation of transaction confirmations.

FISCO BCOS network runs using four consensus nodes that apply the PBFT (Practical Byzantine Fault Tolerance) algorithm, which integrates with distributed storage nodes and cross-chain authentication units. Solidity v0.4.25 is used in the smart contract setting for cross-chain logical execution. The cross-chain system integrates ECDSA-secp256k1 for cryptographic safeguards and specialized anchor nodes possessing load balancing abilities. TLS 1.3 protocol ensures the security of inter-chain communications.

6.4. Performance Comparison Experiment

6.4.1. Detailed Description of the Experimental Control Variables

To confirm the experimental credibility and distinguish the effects of the new architecture components on performance, a structured management system incorporating network, transaction, and system parameters was formulated. This arrangement ensured the network’s topology remained the same in both versions, maintaining a uniform bandwidth distribution of 1 Gbps and synchronized block production intervals of 2 s, thus providing uniformity in network dynamics during the analysis.

Control mechanisms at the transaction level were applied using uniform parameters throughout the experiment. All transactions kept payload sizes consistent at 4 KB, and the complexity of smart agreements was standardized for similar computational needs. This standardization helped avoid disparities in performance metrics arising from varied transaction traits or the necessities for contract execution.

System resource allocation was managed with exactness through consistent Docker container arrangements, evenly apportioning identical CPU and memory resources among various implementations. We carefully oversaw and directed background operations to maintain even system load conditions throughout the experiment. These actions effectively protected the influence of our proposed architectural components against potential system-specific variations.

The comprehensive control approach enabled precise monitoring of performance improvements, thanks to recommended structural progress, guaranteeing consistent experimental outcomes and validity. This systematic method established the foundation for a reliable performance comparison between this proposed approach and current cross-chain methods.

6.4.2. Experiment Results

For creating a stringent framework for comparative analysis, our proposed solution along with the WeCross cross-chain scheme were integrated into the experimental framework outlined in Section 5.3. Adhering to the official documentation guidelines, the WeCross was implemented, incorporating the same hardware setups and network parameters to validate our experiment. This approach facilitates direct performance assessment under controlled environments by removing factors related to infrastructure that could influence experimental results.

During the experiment, the proposed scheme and the WeCross cross-chain scheme are used to operate continuous cross-chain data requests, and the average delay and system throughput of each cross-chain transaction are recorded. The text scheme defaults to complete the previous certificate authentication. During the experiment, the source chain sends the requested content and the signature of the request. After the request is executed, the result is encrypted and returned.

The performance experiment of cross-chain read operation tests the performance of nodes by changing the total amount of requests. The fixed concurrency degree is 10, and the total amount of requests increases by 250 at a time and increases to 5000. The total number of tests is 20 groups, and each group is tested three times. We take the average as a record. The results are shown in Figure 7 and Figure 8.

From the comparison results of the read operation, the scheme in this study shows some advantages in terms of delay and throughput compared with WeCross. The delay fluctuates slightly with the slow increase in the number of requests. Compared with WeCross, the scheme in this study always maintains the advantage of 5–7 ms, but it is about 52 ms slower than single-chain reading, which is mainly due to the consumption of network communication. The throughput increases significantly with the increase in the number of requests, this change is more obvious. It is mainly affected by network consumption and cannot achieve maximum performance at the beginning. In addition, cross-chain requests can be executed by multiple nodes. Although the delay increases, the throughput is significantly improved with the help of the load balancer. In the initial stage, the advantage of this scheme is not obvious. The throughput is in the growth stage but the gap is small before the request amount reaches 1000, After that, the gap gradually increases, and the maximum throughput gap is 58TPS.

The performance experiment of cross-chain write operation also tests the performance of nodes by changing the total amount of requests. The fixed throughput is 10, and each group was tested three times to take the average as a record. The total number of requests increased by 250 at a time, from 1000 to 5000. The total number of tests was 17 groups, and each group was tested three times to take the average as a record. The efficiency comparison results of the write operation are shown in Figure 9 and Figure 10.

Our experiments showed consistent performance improvements across testing cycles. The 5–7 ms reduction in read operation delay (Figure 9) directly results from our refined authentication methods in the distributed trust framework. Similarly, the 58TPS throughput boost (Figure 10) is due to the augmented parallel processing power provided by our cross-chain anchor nodes framework.

To maintain consistent results, every test setup was conducted repeatedly under regulated conditions, averaging the outcomes to reduce statistical discrepancies. The variation in standard deviation through test repetitions stayed under 5%, signifying stable performance traits.

From the comparison results of write operations, the scheme in this study shows some advantages in terms of delay and throughput compared with WeCross. The write operation of the scheme in this study always maintains the advantage of about 26 ms and the performance is also relatively stable. Compared with the single-chain write operation under the same conditions, the delay of cross-chain write operation increases by about 60 ms, which is mainly affected by network communication. The change in throughput is more significant because cross-chain requests can be executed by multiple nodes. Although the delay increases, the throughput is still significantly improved. The throughput of this scheme basically maintains the advantage of 27TPS compared with WeCross.

In addition, unlike the WeCross cross-chain system, this method maintains a read operation delay of 5–7 ms and boosts the throughput up to 58 TPS. In terms of write efficiency, it reduces latency by about 26 ms and boosts throughput by about 27 TPS. The results comprehensively show the significant advantages of the suggested, small-sized, and efficient blockchain cross-chain alliance strategy in reducing computing costs and network traffic.

From the experimental results, it can be seen that the scheme in this study has a greater advantage compared with WeCross, and the scheme is based on the organizational structure of the chain itself for lightweight consideration, so the scheme is more lightweight.

6.4.3. Comprehensive Performance Analysis

We comprehensively assessed our optimization model through rigorous performance evaluation. Experimental results show that our distributed trust model and hybrid anchor node architecture significantly enhanced system performance. Key improvements include a (1) 45% reduction in processing demands through our refined certificate management system; (2) a 58% enhancement in data transfer efficiency; and (3) a 30% reduction in bandwidth usage. The system maintained consistent sub-100 ms latency across all test scenarios, confirming its reliability for large-scale cross-chain interactions.

6.4.4. Scalability Analysis at High Transactions

The preceding performance analysis demonstrates the efficacy of our proposed cross-chain authentication mechanism compared with WeCross in standardized testing environments. However, to provide a comprehensive evaluation of real-world applicability, it is imperative to assess system scalability under high transactional volumes that align with enterprise-level deployment scenarios. This section presents an extended scalability analysis to address this research gap.

To evaluate performance degradation patterns under increasing load, we implemented a progressive load testing framework with transaction volumes ranging from 5000 to 50,000 concurrent requests. The experimental environment maintained consistent hardware specifications as outlined in Table 2, while systematically scaling the following parameters:

1

Concurrent connection count: Progressive scaling from 100 to 1,000 concurrent clients.

2

Transaction complexity: Three distinct transaction profiles (simple read, complex read with joins, write with validation).

3

Network conditions: Simulated network latency variations (10 ms, 50 ms, 100 ms) to represent diverse geographical deployments.

4

Cross-chain throughput ratio: Varied proportions of cross-chain to intra-chain transactions (10%, 30%, 50%)

Table 4. Comparative Analysis of Scalability Metrics between WeCross and Proposed Approach at Maximum Transaction Volume (50,000Concurrent Requests).

Scalability Metric	WeCross	Proposed Approach	Improvement
Sustained Throughput (TPS)	143.2	234.8	64.0%
P95 Latency (ms)	427.6	182.3	57.4%
Resource Utilization (CPU-cores/1000 TPS)	3.8	2.1	44.7%
Maximum Concurrent Connections	764	987	29.2%
Recovery Time After Peak Load (s)	14.2	5.7	59.9%

presents a comprehensive comparison of scalability metrics at the maximum tested transaction volume (50,000 concurrent requests).

The results demonstrate three significant findings:

1

Throughput Scaling: While both systems exhibit some performance degradation at extremely high volumes (>30,000 concurrent requests), our approach maintains 86.3% of baseline throughput at maximum load, compared with 64.7% for WeCross. This represents a 33.4% improvement in throughput preservation under extreme conditions.

2

Latency Stability: Our system demonstrates superior latency stability, with a standard deviation of 18.4 ms across all load conditions, compared with 42.7 ms for WeCross. This latency predictability is particularly crucial for time-sensitive cross-chain applications in financial services and supply chain management.

3

Resource Utilization Efficiency: CPU utilization metrics revealed that our approach requires 28.3% less computational resources per transaction at scale, primarily due to the optimized certificate management system and elimination of Relay-chain validation overhead.

7. Conclusions and Future Work

7.1. Conclusions

This study presents a novel structure for inter-chain exchange in consortium blockchains, focusing on identity verification. This presents a decentralized trust framework that simplifies inter-chain communication without the need for external intermediaries. Our experiment’s verification was conducted in a mock environment using Hyperledger Fabric v2.2 and FISCO BCOS systems, integrating smart contracts in Solidity v0.4.25. Although this experimental setting provided significant insights, it depicted a controlled situation without network latency factors typical in production settings, focusing mainly on read and write processes rather than complex transaction sequences.

The major advancements of this research include replacing traditional Relay systems with cross-chain anchor nodes; creating a multi-layered certificate management system in the CTL framework; establishing a comprehensive smart contract architecture that integrates Certificate Verification Smart Contract (CVSC), Signature Verification Smart Contract (SVSC), Data Encryption Smart Contract (DESC), and Operation Record Smart Contract (ORSC); and developing a Sybil attack prevention system that incorporates trust assessment metrics.

Section 6’s performance analysis uncovered crucial findings: the recommended technique demonstrated a 5–7 ms delay in reading activities and a 26 ms improvement in writing tasks compared with WeCross. Throughput enhancements were particularly notable, with our solution achieving up to a 58 TPS improvement for read operations and 27 TPS for write operations. The implementation of distributed trust models and mixed anchor node frameworks resulted in an approximate 45% reduction in computational load and a 30% decrease in bandwidth consumption, while simultaneously maintaining latency under 100 ms in different scenarios.

The research results confirm our system’s proficiency in aligning security requirements with operational efficiency, providing an efficient, scalable, and secure method for cross-chain interactions in consortium blockchain environments. Through the amalgamation of distributed trust tenets with enhanced certificate handling and smart contract implementation, we lay a solid groundwork for cross-chain communication while maintaining the independence and security features of the blockchain networks involved.

7.2. Future Work

This study lays the groundwork for advancing cross-chain technology within consortium blockchains, yet numerous paths require further exploration. Cross-chain scalability optimization represents a primary research direction, as current implementations face performance constraints when handling large-scale concurrent requests. Upcoming studies should investigate the use of sharding technology in inter-chain scenarios to enhance data processing efficiency through better data division techniques. Additionally, developing advanced dynamic load-balancing algorithms could improve intelligent request scheduling and address performance challenges in high-concurrency scenarios.

The interoperability of smart contracts introduces an additional important area for research. The heterogeneity of smart contract languages and execution environments across blockchain platforms limits the flexibility of cross-chain applications. Future work should focus on cross-chain migration technology and unified contract specification standards to enable seamless interaction between smart contracts deployed on different chains, thereby facilitating more sophisticated cross-chain applications. With the advancement of these technologies, the breadth and intricacy of cross-chain applications are expected to grow, paving the way for novel research in blockchain interoperability.