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Intelligent Internet-of-Things and Cyber-Physical Systems: Theory, Applications, and Security Challenges
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Intelligent Internet-of-Things and Cyber-Physical Systems: Theory, Applications, and Security Challenges

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Communications".

Deadline for manuscript submissions: closed (10 June 2024) | Viewed by 8792

Special Issue Editor

Prof. Dr. Xiangxue Li

E-Mail Website
Guest Editor
School of Software Engineering, East China Normal University, Shanghai 200062, China
Interests: artificial intelligence security; blockchain; Intelligent connected vehicle; cryptography
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

With the rapid development of intelligent technologies, the Internet of Things (IoT) and cyber-physical systems (CPS), as widely used paradigms connecting the physical environment (such as cyber components and sensors) with humans through heterogeneous devices, have shown great advances in many fields, such as transportation systems, digital health, smart agriculture, smart homes, smart grids, and industrial automation.

The integration of the cyber-physical systems with the Internet of Things makes them a hybrid community that requires disruptive technologies for future developments. Artificial intelligence (AI) has already shown great application potential in such a complex and dynamic system, as it can not only help to analyze a large amount of data and provide real-time predictive analysis, but it can also promote efficient decision making through the intelligent management and control of IoT and CPSs. However, security challenges are also emerging in such a heterogeneous system in a continuous sensing environment, privacy preservation, confidentiality, and reliability emerge as key concerns in IoT and CPSs.

This Special Issue will focus on advanced research regarding all fundamental issues in intelligent IoT and CPSs. Researchers are welcome to present original research on the latest findings related to current trends and challenges in the relevant topics. Topics of interest include, but are not limited to, the following:

  • Novel theories and concepts for IoT and CPSs;
  • Artificial Intelligence for IoT and CPSs;
  • Communications and Networking for IoT and CPSs;
  • Trust, Security, and Privacy Issues for IoT and CPSs;
  • Intelligent IoT and CPSs applications;
  • Sensors and Devices for IoT and CPSs;
  • Architectures, paradigms, protocol, and algorithms for IoT and CPSs;
  • Fog/Edge/Cloud Computing for IoT and CPSs;
  • Energy Efficient Technologies for IoT and CPSs.

Prof. Dr. Xiangxue Li
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

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Published Papers (4 papers)

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Research

24 pages, 1720 KiB  
Article
Toward Sensor Measurement Reliability in Blockchains
by Ernesto Gómez-Marín, Luis Parrilla, Jose L. Tejero López, Diego P. Morales and Encarnación Castillo
Sensors 2023, 23(24), 9659; https://doi.org/10.3390/s23249659 - 6 Dec 2023
Cited by 1 | Viewed by 1434
Abstract
In this work, a secure architecture to send data from an Internet of Things (IoT) device to a blockchain-based supply chain is presented. As is well known, blockchains can process critical information with high security, but the authenticity and accuracy of the stored [...] Read more.
In this work, a secure architecture to send data from an Internet of Things (IoT) device to a blockchain-based supply chain is presented. As is well known, blockchains can process critical information with high security, but the authenticity and accuracy of the stored and processed information depend primarily on the reliability of the information sources. When this information requires acquisition from uncontrolled environments, as is the normal situation in the real world, it may be, intentionally or unintentionally, erroneous. The entities that provide this external information, called Oracles, are critical to guarantee the quality and veracity of the information generated by them, thus affecting the subsequent blockchain-based applications. In the case of IoT devices, there are no effective single solutions in the literature for achieving a secure implementation of an Oracle that is capable of sending data generated by a sensor to a blockchain. In order to fill this gap, in this paper, we present a holistic solution that enables blockchains to verify a set of security requirements in order to accept information from an IoT Oracle. The proposed solution uses Hardware Security Modules (HSMs) to address the security requirements of integrity and device trustworthiness, as well as a novel Public Key Infrastructure (PKI) based on a blockchain for authenticity, traceability, and data freshness. The solution is then implemented on Ethereum and evaluated regarding the fulfillment of the security requirements and time response. The final design has some flexibility limitations that will be approached in future work. Full article
(This article belongs to the Special Issue Intelligent Internet-of-Things and Cyber-Physical Systems: Theory, Applications, and Security Challenges)
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45 pages, 4624 KiB  
Article
Securing Smart Healthcare Cyber-Physical Systems against Blackhole and Greyhole Attacks Using a Blockchain-Enabled Gini Index Framework
by Mannan Javed, Noshina Tariq, Muhammad Ashraf, Farrukh Aslam Khan, Muhammad Asim and Muhammad Imran
Sensors 2023, 23(23), 9372; https://doi.org/10.3390/s23239372 - 23 Nov 2023
Cited by 16 | Viewed by 2574
Abstract
The increasing reliance on cyber-physical systems (CPSs) in critical domains such as healthcare, smart grids, and intelligent transportation systems necessitates robust security measures to protect against cyber threats. Among these threats, blackhole and greyhole attacks pose significant risks to the availability and integrity [...] Read more.
The increasing reliance on cyber-physical systems (CPSs) in critical domains such as healthcare, smart grids, and intelligent transportation systems necessitates robust security measures to protect against cyber threats. Among these threats, blackhole and greyhole attacks pose significant risks to the availability and integrity of CPSs. The current detection and mitigation approaches often struggle to accurately differentiate between legitimate and malicious behavior, leading to ineffective protection. This paper introduces Gini-index and blockchain-based Blackhole/Greyhole RPL (GBG-RPL), a novel technique designed for efficient detection and mitigation of blackhole and greyhole attacks in smart health monitoring CPSs. GBG-RPL leverages the analytical prowess of the Gini index and the security advantages of blockchain technology to protect these systems against sophisticated threats. This research not only focuses on identifying anomalous activities but also proposes a resilient framework that ensures the integrity and reliability of the monitored data. GBG-RPL achieves notable improvements as compared to another state-of-the-art technique referred to as BCPS-RPL, including a 7.18% reduction in packet loss ratio, an 11.97% enhancement in residual energy utilization, and a 19.27% decrease in energy consumption. Its security features are also very effective, boasting a 10.65% improvement in attack-detection rate and an 18.88% faster average attack-detection time. GBG-RPL optimizes network management by exhibiting a 21.65% reduction in message overhead and a 28.34% decrease in end-to-end delay, thus showing its potential for enhanced reliability, efficiency, and security. Full article
(This article belongs to the Special Issue Intelligent Internet-of-Things and Cyber-Physical Systems: Theory, Applications, and Security Challenges)
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25 pages, 3049 KiB  
Article
A Lightweight Unsupervised Intrusion Detection Model Based on Variational Auto-Encoder
by Yi Ren, Kanghui Feng, Fei Hu, Liangyin Chen and Yanru Chen
Sensors 2023, 23(20), 8407; https://doi.org/10.3390/s23208407 - 12 Oct 2023
Cited by 7 | Viewed by 1985
Abstract
With the gradual integration of internet technology and the industrial control field, industrial control systems (ICSs) have begun to access public networks on a large scale. Attackers use these public network interfaces to launch frequent invasions of industrial control systems, thus resulting in [...] Read more.
With the gradual integration of internet technology and the industrial control field, industrial control systems (ICSs) have begun to access public networks on a large scale. Attackers use these public network interfaces to launch frequent invasions of industrial control systems, thus resulting in equipment failure and downtime, production data leakage, and other serious harm. To ensure security, ICSs urgently need a mature intrusion detection mechanism. Most of the existing research on intrusion detection in ICSs focuses on improving the accuracy of intrusion detection, thereby ignoring the problem of limited equipment resources in industrial control environments, which makes it difficult to apply excellent intrusion detection algorithms in practice. In this study, we first use the spectral residual (SR) algorithm to process the data; we then propose the improved lightweight variational autoencoder (LVA) with autoregression to reconstruct the data, and we finally perform anomaly determination based on the permutation entropy (PE) algorithm. We construct a lightweight unsupervised intrusion detection model named LVA-SP. The model as a whole adopts a lightweight design with a simpler network structure and fewer parameters, which achieves a balance between the detection accuracy and the system resource overhead. Experimental results on the ICSs dataset show that our proposed LVA-SP model achieved an F1-score of 84.81% and has advantages in terms of time and memory overhead. Full article
(This article belongs to the Special Issue Intelligent Internet-of-Things and Cyber-Physical Systems: Theory, Applications, and Security Challenges)
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34 pages, 2786 KiB  
Article
Provenance-Based Trust-Aware Requirements Engineering Framework for Self-Adaptive Systems
by Hyo-Cheol Lee and Seok-Won Lee
Sensors 2023, 23(10), 4622; https://doi.org/10.3390/s23104622 - 10 May 2023
Cited by 1 | Viewed by 1811
Abstract
With the development of artificial intelligence technology, systems that can actively adapt to their surroundings and cooperate with other systems have become increasingly important. One of the most important factors to consider during the process of cooperation among systems is trust. Trust is [...] Read more.
With the development of artificial intelligence technology, systems that can actively adapt to their surroundings and cooperate with other systems have become increasingly important. One of the most important factors to consider during the process of cooperation among systems is trust. Trust is a social concept that assumes that cooperation with an object will produce positive results in the direction we intend. Our objectives are to propose a method for defining trust during the requirements engineering phase in the process of developing self-adaptive systems and to define the trust evidence models required to evaluate the defined trust at runtime. To achieve this objective, we propose in this study a provenance-based trust-aware requirement engineering framework for self-adaptive systems. The framework helps system engineers derive the user’s requirements as a trust-aware goal model through analysis of the trust concept in the requirements engineering process. We also propose a provenance-based trust evidence model to evaluate trust and provide a method for defining this model for the target domain. Through the proposed framework, a system engineer can treat trust as a factor emerging from the requirements engineering phase for the self-adaptive system and understand the factors affecting trust using the standardized format. Full article
(This article belongs to the Special Issue Intelligent Internet-of-Things and Cyber-Physical Systems: Theory, Applications, and Security Challenges)
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