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12 November 2021

Distributed Hybrid Double-Spending Attack Prevention Mechanism for Proof-of-Work and Proof-of-Stake Blockchain Consensuses

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and
1
Research Department, Idenitive Mashable Prototyping, Banyumas 53124, Indonesia
2
Department of Computer and Information Sciences, Universiti Teknologi PETRONAS, Seri Iskandar 32160, Malaysia
3
College of Computer and Information Sciences, Prince Sultan University, Riyadh 11586, Saudi Arabia
*
Author to whom correspondence should be addressed.
This article belongs to the Special Issue Blockchain: Applications, Challenges, and Solutions

Abstract

Blockchain technology is a sustainable technology that offers a high level of security for many industrial applications. Blockchain has numerous benefits, such as decentralisation, immutability and tamper-proofing. Blockchain is composed of two processes, namely, mining (the process of adding a new block or transaction to the global public ledger created by the previous block) and validation (the process of validating the new block added). Several consensus protocols have been introduced to validate blockchain transactions, Proof-of-Work (PoW) and Proof-of-Stake (PoS), which are crucial to cryptocurrencies, such as Bitcoin. However, these consensus protocols are vulnerable to double-spending attacks. Amongst these attacks, the 51% attack is the most prominent because it involves forking a blockchain to conduct double spending. Many attempts have been made to solve this issue, and examples include delayed proof-of-work (PoW) and several Byzantine fault tolerance mechanisms. These attempts, however, suffer from delay issues and unsorted block sequences. This study proposes a hybrid algorithm that combines PoS and PoW mechanisms to provide a fair mining reward to the miner/validator by conducting forking to combine PoW and PoS consensuses. As demonstrated by the experimental results, the proposed algorithm can reduce the possibility of intruders performing double mining because it requires achieving 100% dominance in the network, which is impossible.

1. Introduction

Blockchain technology has been widely used in various distributed system contexts, including content distribution networks [1], smart grid systems [2], e-healthcare [3], real estate [4,5], e-finance [6], e-education [7], supply chains, e-voting, smart homes [8,9], smart cities [10] and smart industries [11,12]. The advent of blockchain technology has affected the global financial system through digital currencies. In 2008, Satoshi Nakamoto invented a revolutionary electronic cash system called Bitcoin (a digital currency) that made peer-to-peer electronic transactions possible. This peer-to-peer digital currency system was designed to eliminate the need for third parties in financial transactions between unknown parties in a trustworthy and verifiable way [13]. In January 2009, the same group created software as an open-source code and introduced the first digital currency in history [14]. As the fundamental technology of Bitcoin, blockchain consists of a transparent and immutable list of chained blocks of transactions. In the peer-to-peer network, each peer maintains a copy of the blockchain known as the distributed ledger.
Blockchain acts as a decentralised public ledger for recording data as blocks, which constitute a connected list data structure used to indicate logical relationships between the data added to the blockchain. The data blocks can be retained without the involvement of a centralised agency or intermediary. In another alternative, data blocks are copied and exchanged throughout the entire blockchain network, thereby eliminating device failure, data management and cyber-attacks. The two most important processes of blockchain are block mining and block validation. The mining process involves adding a new block or transaction to the public global ledger. The new block or transaction is then validated in a process known as block validation. To understand how blockchain operates, we need to understand its four underlying layers. At the lowest layer are peers sign transactions, which represent an agreement between two parties, such as exchanging physical or digital property or completing a task. To ensure the absence of corrupt branches and divergences [15], the nodes must agree on which transactions should be kept in the blockchain, which is the responsibility of the consensus layer. The third layer is the compute interface. Through the compute interface, the blockchain is able to provide increased functionality. Blockchain maintains a record of each transaction undertaken by a user so that by calculating the balance of each user, the overall balance may be determined. The last layer, governance, extends the blockchain architecture to human interaction in the physical realm. Therefore, the popularity of blockchain is inevitable because the technology can provide desirable features by replacing the centralised communication architectures of today. The core protocol of blockchain, particularly in blockchain-based cryptocurrencies, refers to the consensus protocol. The consensus protocol enables all peers to agree on every block inclusion in the distributed ledger [16]. As a result of a consensus mechanism, all truthful nodes establish mutual agreement on a consistent ledger in asynchronous, untrusted networks [17]. The consensus protocols are well-defined, but inputs from various stakeholders are also considered, which affects the blockchain’s authenticity. Incorporating new methods for improving consensus protocols and/or patching systems is therefore essential to the development of blockchains.
Different consensus mechanisms are required to ensure the security of digital transactions due to the varying types of blockchain technology [18]. A common consensus mechanism is proof-of-work (PoW), in which the parties must demonstrate their rights to add a node by solving an increasingly complicated computational problem to ensure authentication and compliance, including identifying thresholds for harm, such as leading zeros [19]. Given that the PoW protocol needs tremendous computing power to solve the block complexity in Bitcoin [20], another consensus protocol called proof-of-stack (PoS) was proposed to overcome the problems of the PoW protocol. Despite the high complexity of the PoS consensus, this protocol may be vulnerable to stack problems if more than half of the network is manipulated to prevent a new block from being distributed to confirm transactions [21]. A PoS protocol separates stake blocks according to the relative hashing rates of miners (i.e., their computational power) in relation to the resource capacity of existing miners [22]. This approach makes the choice fair and prevents the richest participant from dominating the network. Many blockchains, such as Ethereum [23], opt for PoS because power consumption and scalability are greatly reduced. Several consensus approaches, including Byzantine fault tolerance (BFT) and its variants, are also available [24].
However, despite the application of consensus protocols, which prevent many security breaches, several malicious attacks have occasionally hampered the growth of blockchain technology. For example, certain attacks, such as Eclipse, Sybil, BGP deterrence, and 51%, are triggered as a result of attempts to penetrate the blockchain network. Amongst these attacks, the 51% attack has received the least attention from researchers due to its high costs. However, recent security incidents have demonstrated that 51% attacks can be carried out against various contemporary cryptocurrencies [25]. Compared with other consensus protocols, PoW immediately challenges 51% attacks, where recent attacks have mainly focused on PoW-dependent cryptocurrencies [26]. This is one of the most severe dangers associated with a PoW-based cryptocurrency because it assumes that if a fraudulent peer network is allowed to obtain more than 50% of the network assets (i.e., computing power), its members become the majority of the network’s decision makers. Peers with superior processing skills could dominate the network because they have the capability to mine numerous blocks as peers compete for fast access. They can easily exploit the blockchain by creating fake transactions, and the fraud perpetrated by other users may result in large-scale financial losses.
To prevent this attack, researchers have performed various studies. The majority of them recommended combining two or more resource proofs into a hybrid protocol to combat this attack [27,28,29,30,31]. However, mixing two or more existing protocols (hybrid protocol) makes the network resistant to this attack. Therefore, the recent implementation of hybrid protocols has other challenges and drawbacks that need to be addressed. For example, several have added voting systems, ticket delivery systems, fines, special nodes and block validator groups to deter malicious behaviour [32]. These measures are successful in protecting the network against 51% attacks. However, their primary weakness is in rewarding block mining to investors, which pertains to the number of Bitcoins you receive if you are successful in mining a block. Undoubtedly, the investor invests his hard-earned money in a cryptocurrency to reap the benefits of his investment. These benefits may be derived from the block mining reward. In this scenario, the accuracy of the block generation time interval is crucial in ensuring that this benefit is delivered to the appropriate consumer at the appropriate time. However, the voting, ticket and other systems are not time-controlled, and no consistent distribution of benefits occurs over the block reward generation intervals. Another major issue is the diversification of peers by establishing special committees and validation groups that violate the P2P network’s principle.
Hence, this study proposes a hybrid consensus protocol that integrates PoW and PoS to control block generation time in two ways. Firstly, our proposed model uses the PoW mining method for the first time to prevent the block generation time from exceeding a specified threshold. Secondly, the generated block is validated by the PoS consensus without any need for voting or commission approval. In the proposed model, each block is validated by the entire network. Hybridisation is one of the aspects that make our study unique and novel compared with previous studies. In addition to being able to handle the 51% attack, the framework ensures a standardised distribution of mining rewards to stakeholders and investors by maintaining a precise block generation interval with difficulty adjustment in PoW mining and stakeholder probability calculation based on their mature stake balance. This study proposes a hybrid algorithm that combines the PoW and PoS mechanisms to ensure a fair mining reward between the miner and validator by controlling the block generation time. To ensure long-term sustainability, the proposed model entails a complexity analysis. The important contributions of this work can be summarised as follows:
  • We evaluated three security protection measures that are specific to the 51% attack and demonstrated their vulnerabilities to exploitation by the 51% attack.
  • We proposed a model to control the block generation time with the distributed validation technique, which enhances blockchain security and performance.
  • We hybridised PoW and PoS consensuses to solve the above-mentioned issue for the fair mining and stacking mechanism, which by default prevents the 51% attack.
This paper is structured as follows. Section 2 presents a background of the topic and related work wherein blockchain and previous attempts are described and investigated. Section 3 provides an overview of the methodology adopted in this study and a description of the experiment’s algorithms. The analysis and results are given in Section 4, and the conclusions and future work directions are presented in Section 5.

3. Proposed Hybrid Approach

In this study, we combine two consensus mechanisms for a fair mining reward for the miner and validator into a hybrid model. Assume that the behaviour of nodes is likely to be known as the most massive chain. As a result, the first block generated in this model is usually referred to as the main chain, along with the majority of the nodes in the network. In Figure 4, we present our proposed finite state automata (FSA) model for the block-forging process.
Figure 4. FSA for the block-forging process.
In Figure 4, the square blocks correspond to PoW, and the circles correspond to PoS. The arrows represent canonical chains. Under certain conditions, PoW and PoS blocks are mined and staked in random order, and the possibility of reaching a consensus is approximately 50% [41]. Nx is the set of all positive integers smaller than 2x, and block b = (fp,fsr,ftr,fd,fts,ftx), where fp,fsr,ftr,fd ∈ N256, fd ∈ N64 and ftx is a linked list. Table 3 provides a description of these elements.
Table 3. Description of the elements of the proposed algorithm.
Miners working in a conventional PoW mining setup require a step-by-step implementation, as depicted in Algorithm 1. With the mining difficulty parameter dw and the 256-bit-long function hash(·), miners can solve complex problems within this rule, as shown in Equation (1).
hit = hash(b) ≤ 2256/dw
After completing mining, several rewards are provided, and their mining power is proportional to the computation power.
Algorithm 1. Mining for the PoW mechanism
1Procedure MINING PoW (δ)
2k ← GetBestChain
3z1 ← GetLastBlock(k)
4z2 ← GetSecondLastBlock(k)
5diff ← GetComplexity(z1,z2)
6trxs ← GetMemoryPoolTrxs()
7z ← CreateBlockTemplate(k,trxs)
8            do
9thesolution ← ProofofWork(z)
10while thesolution > 2256/diffs
11z ← Finalize(z,thesolution)
12Import & Propagate(z)
13    end
Figure 5 illustrates the proposed hybrid model flow, in which the mining process begins with the identification of stake parameters. These are mature balancing parameters for stakes, coinage, the synchronisation of timestamps, the weights of individual nodes and the weight of the entire network. After the initial validations and time sync prerequisite tests, we add the PoW nonce discovery loop. Next, an empty block template is created. The PoW loop then locates a valid nonce to generate a valid hash. The block contains individual transactions that cannot be arbitrarily modified. Other block records, such as timestamps and earlier hash blocks, are irreversible. Therefore, to adjust the hash and achieve a correct pattern, the nodes use the nonce arbitrary field. As part of the PoW loop, miners start with 0 and continue to increase the nonce and produce hashes whilst merging this nonce with other block data. When a correct hash that meets the requirements of the block hash is discovered, the peer achieves success in mining. A complexity factor is added for the block interval to be preserved.
Figure 5. Process of the proposed hybrid model with supported features.
By applying this approach, we can achieve excellent control over the generation time interval for blocks. In addition, the benefits of mining and transaction fees are evenly distributed amongst investors. Apart from this mining method, another security measure is implemented to secure the network against the misbehaviour of nodes by preventing these nodes in a predefined period. A minimum of one hour is required to ban the simulation setting. Whenever a peer node obstructs, the peer is banned for one hour from the network. The protocol imposes an additional restriction that all nodes must be fairly validated. Both network nodes are equally weighted with regard to decision making. It involves validating a rich node and judging a weak node fairly. The two peer nodes share the same code and weight. Given that the mining process involves a degree of risk, every node can verify transactions and blocks. The frequency of the chance depends on its staking capacity.
Furthermore, our proposed method incorporates PoS and PoW into a stochastic coherence process without sacrificing availability, and a decentralised stack is essential. Considering that the systems run based on computations and stakes in the network, we define a rule-based forking mechanism to ensure that new blocks are produced between the two consensus types. By examining how much effort is made and the rewards obtained by stacker and miner devices, which should be fair, this study demonstrates its novelty. This simulation proposes a minor tweak to the difficulty adjustment, as indicated in Equation (2).
tds, c0 = argmax tdwi · tdsi; i ∈ {1,...,N}
In general, the algorithm chooses the appropriate complexity to match the inside network’s hash/stake power. However, this choice is sometimes gradual. Consider, for example, that stake complexity is approximately 10 times greater than miner complexity. There is a 10x increase in stake in comparison with its hash rate. Unlike PoW, each stacker processes several numbers and keys.
seedt+1 = sign(seedt,sk)
When this condition is met, a stake block can be produced.
ln(hash(seed)/2256) | · dsV · ∆,
where V is the amount of the computation unit and ∆ is the time from the last block. To define the algorithm target, we should have t as the target time and 2t becomes the target time for PoS and PoW. Double-spending attacks take place when an individual has more than 51% of the peer network either as a miner or as a stacker. The dominant attacker is assumed to have power defined with a and b notations, and the ordinary nodes are defined with c and d notations. The hash (PoW) block generation rate is λ ω = ω d ω , where (w) is the hash rate. During the simulation, the number of blocks were generated using random variable XPoS(λw), and E(X) = λw. For example, assume that Yw is a notation of the total difficulty of the mining process; thus, E(Yw) = E(X) · dw.
E ( Y ω ) = w d ω d ω = w
Similarly in Algorithm 2, the PoS block generation rate is declared as λ ω = s d s , where s is the amount of stake.
The notation Ys is the total stack difficulty.
E ( Y s ) = w d s d s = s
Meanwhile, the attacker’s chain contains a weight within the expected period.
(tdwc + a · t) · (tdsc + b · t)
The ordinary nodes’ rules are defined as follows:
(tdwc + c · t) · (tdsc + d · t),
where tdw and tds represent the total difficulty/complexity of mining and stacking blocks, respectively. According to the prospectus of the attacker, overtaking another chain requires the attacker to possess greater power than the normal nodes, which results in network inequality.
tdsc · (a − c) + tdwc · (b − d) + (ab − cd) · t ≥ 0.
Algorithm 2. Stacking Algorithm
1Procedure STAKEBLOCK(δ,pk,sk)
2k ← GetBestNode
3z1 ← GetLastBlock(k)
4z2 ← GetSecondLastBlock(k)
5stakes ← GetPoStake(k,pk)
6diffs ← GetComplexity(z1,z2)
7tms ← GetTimestamp(z1)
8seeds ← GetSeed(z1)
9seeds ← Sign(seeds,sks)
10∆ ← diffs · ln(hash(seeds)/2256)/stake
11Do
12sleep(1)
13  While φ < tms + ∆
14trxs ← GetMemoryPoolTrxs()
15z ← CreateBlockTemplate(k,trxs,seeds)
16z ← Final(z,sk)
17Import & Propagate(z)

Double Spending Attack Prevention Scenario

Only when both a PoW block and a PoS block confirm a transaction should it be considered confirmed on the blockchain. A transaction should not be considered confirmed when only PoS blocks confirm it because PoS blocks can be minted over multiple conflicting chains. As long as people refrain from erroneously considering 1-PoS-confirmed transactions as confirmed, this should not be an issue.
Furthermore, a transaction should not be considered confirmed when only PoW blocks confirm it because this could lead to double spending by an attacker using a 51% attack. This attack is much harder than double spending for someone accepting only PoS blocks as confirmation, but it is likely to be much easier than it is for today’s Bitcoin because the new algorithm reduces the cost of mining (which in turn reduces the system’s hash power by nature). For this reason, both PoW and PoS should be used to confirm or finalise transactions.
The expenditures required to launch a 51% attack are much greater than those for PoW for a given amount of honest mining. Hence, an attacker requires an amount of hash power equal to the honest hash power (which in an equilibrium case results in the attacker possessing 100% of the hash power). In addition, an attacker needs to own a considerable amount of hash stake. Given that the longest chain is determined by multiplying PoW and PoS accumulated difficulties, even if a single miner accumulates 90% of the mining power, it would not be able to produce a significantly longer chain without also owning more than 11% of current coins in circulation.
Considering a scenario in which the attacker attempts to create an additional sidechain and reveals it at a, we assume that the attacker has a hash power and stake power of (a,b), and the fair nodes have (c,d). Let Y w be the total mining difficulty. Then, E ( Y w ) = E ( X ) d w . This has been given in Equation (1), where the PoS block generation rate λ w = n d 2 , where s is the stake and Y s is the total mining difficulty presented in Equation (6). The total mining difficulty is an integration of the hash rate over time and vice versa of the stake over time. In duration t , the malicious chain has an expected weight of ( t d w c + a t ) ( t d s c + b t ) , and the fair nodes’ chain has ( t d w c + c t ) ( t d s c + d t ) , where t d w and t d s are the total difficulty for PoW and PoS from the genesis block, respectively.
For the attacker to gain the fair nodes’ chain, the malicious nodes need to have a longer chain than the fair nodes’ chain, which further leads to the following inequality: l d s c ( a c ) + l d w c ( b d ) + ( a b c d ) l 0 . Given that this attack can only occur if the creation of blocks is free, we assume that the attacker will attempt to attack by using only PoS blocks. Assume that
t d a = i = 1 . . I I w n d w i · j = 1 I s d s j = ( ( H w n ) · d w ¯ ) · ( H s · d s ¯ ) ,
where t d a indicates the total complexity of the malicious chain. Even if the attacker holds the entire active stake and the total voting power remains unchanged, the best-case scenario is an identical td for the main chain. The projected maximum number of blocks that the LRA can create is ( ϕ t N w n ) / 2 t because the protocol forbids the creation of new blocks. If an attacker can increase his stake power through block rewards, then his chances of success increase with time. Specifically, the assailant must reach
( H s ( d s ¯ + Ω ) ) > ( H w d w ¯ ) ( H s d s ¯ )   Ω > H w d w ¯ H s .
Assuming that the primary chain’s forging power is static (i.e., not subject to change), N w = N s is modified to reflect the extra power an attacker would require to equal the main chain’s strength (expressed in difficulty). It must be more challenging than the PoW chain itself. Further research is required to determine how long it takes an attacker to gain access to increased difficulty, but the premise is that this process of gaining power gradually via block rewards occurs over a long period.

4. Experimental Results

During the implementation phase, we set the simulation in such a way that the hash output is uniformly distributed between miners and stakes. The difficulty was adjusted to α = 0.01, the stacker power was set to S = [80, 40, 20, 15, 10, 5, 5, 5, 5, 5] and the miner power was set to M = [32, 16, 8, 6, 4, 2, 2, 2, 2, 2, 2]. Numbers have already been set to show the linearity of the exponential rise in computational power. To begin with, the block time was set to 20 s in t, with a duration of 90 days per entire chain.
During the simulation, a total of 385,479 blocks were generated, out of which 192,688 were stake blocks and 192,791 were mining blocks. As shown in Figure 6, the rewards were proportional to computing power (stake/mining), which was considered a fair outcome. The target block time was 20 s, resulting in a stake block time of 40 s and a mining block time of 40 s with an average rate of PsS s/ds, PmM m/dm and PsS s/ds + PmM m/dm.
Figure 6. Experimental results of (a) stake power vs. block rewards distribution and (b) hash power vs. block rewards distribution.
During the experiment, which we ran on the Google Colab platform, we determined that the initial simulation would consume not more than 200 MB of RAM, as shown in Table 4.
Table 4. Machine computational power.
Figure 6a,b illustrate the stake and hash power results over the block rewards distribution. The mean and standard deviation of time are presented in Table 5.
Table 5. Mean and standard deviation of time.
According to the simulation results, the attacker side that dominates the network with more than 51% computation power cannot easily launch the attack because the fork mechanism has a split rule between PoW and PoS implementations. Hence, to take over this network and launch an attack, the attacker needs to command over 100% of the system, which is impossible on a consensus blockchain node. Figure 7 shows that the chain power is demonstrated over the block time generation and distribution, and Figure 8 shows the proposed hybrid model computational power over PoW and PoS block time distributions.
Figure 7. Power vs. block time distribution.
Figure 8. Experimental results of (a) computational power vs. PoS block time distribution and (b) computational power vs. PoW block time distribution.
We began the simulation experiment and based on previous data, we set the computational power for mining to 76, which is the same block size. The results are shown in Table 6.
Table 6. Miners’ computational power before implementing the proposed hybrid mechanism.
Additionally, we discovered that the combined PoW and PoS protocol limits the effective computational power to 52.31. The results of the miner computational power needed for the hybrid mechanism are presented in Table 7.
Table 7. Miners’ computational power with the proposed hybrid mechanism (PoW and PoS).
Mining power and actively minting coins may also be used to calculate the attack’s cost. They may be used as a rough estimate of the cost of mining power because they are closely related to miner earnings (fees and coin base incentives). The active stake can be determined because the amount of Satoshi released every second is inversely proportional to the stake difficulty. By dividing the amount of Satoshi issued into equal parts for each PoS block, we can estimate the total amount of Satoshi currently being mined. To compute the income per block required to sustain the attack cost, these measures may be used to determine an attack–cost objective (e.g., a particular number of Bitcoins or a certain percentage of the total number of Bitcoins mined to date). In turn, this information can be used to dynamically alter the block size and ensure that the block income continues to support the set attack cost goal. Therefore, mining earnings will be increasingly predictable, a certain degree of security will be maintained, and costs will be reduced.
The majority of honest minters make the mistake of making coins on a chain that they believe will last the longest, only to have their efforts thwarted by a competitor’s longer chain. This situation means that several law-abiding minters are penalised for minting. If the fine does not exceed the revenue from minting one block, the expected revenue from the effort to mint should exceed zero. A small fee is likely to have a substantial impact, so the projected revenue from minting should be equal to the overall revenue from minting. Ultimately, this depends on whether dishonest minting on a short chain benefits the dishonest minter. Therefore, how much of a penalty should be imposed is debatable.
Given that PoS blocks have little influence on whether an attacker will be successful in performing an orphan-based mining monopoly attack unless the attacker controls a substantial portion of the coins actively being mined, punishing minters who minted over another PoS block would double the collateral damage. Consequently, minter punishment proofs will be invalid if the most recent PoW block is shared by the minted block and the current block. Further research is needed to determine how much stake an attacker needs to possess in order to perform a mining monopoly attack effectively.
If a PoW block has more than one option (e.g., a collision leaving one orphaned), minters may refuse to mint so as to avoid the penalty. If they do so, they will miss out on the most probable benefit of their actions (which would be much greater). Therefore, the likelihood of this behaviour occurring is very low because the predicted benefits exceed 0 by a factor of two.

5. Conclusions

Bitcoin’s popularity and success are primarily related to the underlying blockchain technology, which is a genuinely unchanging and highly protected distributed ledger governed by a peer-to-peer consensus. This study conducted a comprehensive analysis to build the hybrid cryptocurrency PoW-PoS, which can resolve the 51% attack in the most feasible and advanced way possible. The proposed hybrid model can prevent the attack by mixing PoW and PoS in one thread with a strict time spacing for block generation to achieve a resilient and robust agreement amongst P2P network nodes and guarantee a benefit distribution that is in line with stakeholders’ investment ratios. The results showed that we successfully implemented a hybrid consensus protocol for blockchain that combines mining and stacking. The hybrid protocol creates a fair mechanism for miners and stakers. Furthermore, each block’s period is added to provide a double-spending function for every distribution even though the attacker has more than 51% control over the network. We examined the shortcomings of consensus protocols and security techniques to reveal their main weaknesses. A hybrid model that combines PoW and PoS was then successfully implemented. The system incorporates hardware and economic security without compromising availability, predictability or decentralisation. According to the empirical evidence provided in results Section 4, the proposed protocol is fair and scalable to an arbitrary number of miners and stakes.
In the future, we will conduct a more comprehensive analysis of network stability with additional types of miners and stackers and another simulation based on game theory. A highly economical approach for all mechanisms will also be explored in the future.

Author Contributions

Conceptualization, N.A.A. and A.M.; methodology, N.A.A. and A.M.; software, N.A.A.; validation and formal analysis, N.A.A., A.M. and S.M.F.; investigation, A.M. and S.M.F.; writing—original draft preparation, N.A.A. and A.M.; writing—review and editing, S.M.F. and N.E.; visualization, N.A.A. and A.M.; supervision, S.M.F.; project administration, A.M.; Funding N.E. All authors have read and agreed to the published version of the manuscript.

Funding

The authors would like to acknowledge the support of Prince Sultan University for paying the article processing charges (APC) of this publication.

Institutional Review Board Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

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