Blockchain and Artificial Intelligence for Cyber Security in the Era of IoT and IIoT Applications

A special issue of Journal of Sensor and Actuator Networks (ISSN 2224-2708). This special issue belongs to the section "Network Security and Privacy".

Deadline for manuscript submissions: closed (28 April 2023) | Viewed by 30407

Special Issue Editors


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Guest Editor
Institut de Recherche Dupuy de Lôme (UMR CNRS 6027 IRDL), University of Brest, 29238 Brest, France
Interests: fault detection and diagnosis; failure prognosis; cyberattack detection; fault-resilient control; machine learning
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Special Issue Information

Dear Colleagues,

The 5th revolution of the industrial era – or Industry 5.0 – is the new industry trend that defines the smart factory concept. This concept is based on emerging technologies, such as 5G/6G communications, fog computing, drones, cloud computing, blockchain, artificial intelligence, deep learning, etc. To allow optimization of operations and reduced costs, these technologies are employed to establish a connection between machines and the Internet, through the Internet of Things, and to collect information in the cloud and edge and then process them using artificial intelligence algorithms. However, with thousands of IoT-based devices deployed in the open field, there are many new cybersecurity threats in Industry 5.0. When an adversary attempts to penetrate the network, it uses several different approaches, such as DDoS attacks, scanning attacks, and false data injection attacks, to disrupt the functioning of the IoT-based devices. To protect Industry 5.0 from destruction, change, unauthorized access, or attack, security researchers propose using an intrusion detection system (IDS) combined with blockchain technology. The IDS system is a mechanism for monitoring network traffic, and it is used to detect suspicious or abnormal activities and then enables preventive measures for intrusion risks. Blockchain technology is used to detect fraudulent transactions.

In this Special Issue, both research and practical aspects of blockchain and artificial intelligence methods for cybersecurity are of interest. Aligned with the interdisciplinary nature of cybersecurity, authors from academia, governments, and industry are welcome to contribute. We seek original and high-quality submissions on, but not limited to, one or more of the following topics:

  • Blockchain-based artificial intelligent systems for IoT/IIoT applications
  • Applied cryptography
  • Federated learning for cybersecurity
  • Decentralized learning for cybersecurity
  • Blockchain-based IoT/IIoT applications
  • Blockchain-based Internet of Things architectures and protocols
  • Theory of blockchain in cybersecurity for IoT/IIoT applications
  • Cyber attacks on blockchain and AI
  • Authentication, access control, and authorization
  • Intrusion detection systems for IoT/IIoT applications
  • Deep learning for cybersecurity
  • Machine learning and computer security
  • Privacy-enhancing technologies
  • Machine learning-enabled IoT Security

Dr. Mohamed Amine Ferrag
Prof. Dr. Leandros Maglaras
Prof. Dr. Mohamed Benbouzid
Guest Editors

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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. Journal of Sensor and Actuator Networks is an international peer-reviewed open access semimonthly journal published by MDPI.

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Keywords

  • blockchain
  • cybersecurity
  • deep learning
  • machine learning
  • artificial intelligence
  • IoT
  • IIoT

Published Papers (10 papers)

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Editorial

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3 pages, 162 KiB  
Editorial
Blockchain and Artificial Intelligence as Enablers of Cyber Security in the Era of IoT and IIoT Applications
by Mohamed Amine Ferrag, Leandros Maglaras and Mohamed Benbouzid
J. Sens. Actuator Netw. 2023, 12(3), 40; https://doi.org/10.3390/jsan12030040 - 11 May 2023
Cited by 6 | Viewed by 2219
Abstract
The fifth revolution of the industrial era—or Industry 5 [...] Full article

Research

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24 pages, 1075 KiB  
Article
Distributed Ledger as a Service: A Web 3.0-Oriented Architecture
by Francesco Chiti and Giorgio Gandini
J. Sens. Actuator Netw. 2023, 12(4), 57; https://doi.org/10.3390/jsan12040057 - 20 Jul 2023
Cited by 4 | Viewed by 1455
Abstract
This paper proposes a general and interoperable Web of Things (WoT)-oriented architecture to support a distributed storage application. In particular, the focus is on a distributed ledger service dedicated to machine-to-machine (M2M) transactions occurring in an intelligent ecosystem. For this purpose, the basic [...] Read more.
This paper proposes a general and interoperable Web of Things (WoT)-oriented architecture to support a distributed storage application. In particular, the focus is on a distributed ledger service dedicated to machine-to-machine (M2M) transactions occurring in an intelligent ecosystem. For this purpose, the basic functional modules have been characterized and integrated into a comprehensive framework relying on an IOTA approach. Furthermore, a general protocol that is built upon an underlying publish-and-subscribe framework is proposed to support all the application phases. The proposed approach has been validated by a simulation campaign targeting the achievable latency and throughput and, further, by a qualitative analysis of high-level metrics, both pointing out several advantages in terms of interoperability, scalability, and mobility support, together with addressing some constraints affecting service availability and security. Full article
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19 pages, 2390 KiB  
Article
Energy-Efficient Relay Tracking and Predicting Movement Patterns with Multiple Mobile Camera Sensors
by Zeinab Hussein and Omar Banimelhem
J. Sens. Actuator Netw. 2023, 12(2), 35; https://doi.org/10.3390/jsan12020035 - 13 Apr 2023
Cited by 4 | Viewed by 1507
Abstract
Camera sensor networks (CSN) have been widely used in different applications such as large building monitoring, social security, and target tracking. With advances in visual and actuator sensor technology in the last few years, deploying mobile cameras in CSN has become a possible [...] Read more.
Camera sensor networks (CSN) have been widely used in different applications such as large building monitoring, social security, and target tracking. With advances in visual and actuator sensor technology in the last few years, deploying mobile cameras in CSN has become a possible and efficient solution for many CSN applications. However, mobile camera sensor networks still face several issues, such as limited sensing range, the optimal deployment of camera sensors, and the energy consumption of the camera sensors. Therefore, mobile cameras should cooperate in order to improve the overall performance in terms of enhancing the tracking quality, reducing the moving distance, and reducing the energy consumed. In this paper, we propose a movement prediction algorithm to trace the moving object based on a cooperative relay tracking mechanism. In the proposed approach, the future path of the target is predicted using a pattern recognition algorithm by applying data mining to the past movement records of the target. The efficiency of the proposed algorithms is validated and compared with another related algorithm. Simulation results have shown that the proposed algorithm guarantees the continuous tracking of the object, and its performance outperforms the other algorithms in terms of reducing the total moving distance of cameras and reducing energy consumption levels. For example, in terms of the total moving distance of the cameras, the proposed approach reduces the distance by 4.6% to 15.2% compared with the other protocols that do not use prediction. Full article
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25 pages, 4161 KiB  
Article
Smart Automotive Diagnostic and Performance Analysis Using Blockchain Technology
by Ahmed Mohsen Yassin, Heba Kamal Aslan and Islam Tharwat Abdel Halim
J. Sens. Actuator Netw. 2023, 12(2), 32; https://doi.org/10.3390/jsan12020032 - 7 Apr 2023
Cited by 3 | Viewed by 3046
Abstract
The automotive industry currently is seeking to increase remote connectivity to a vehicle, which creates a high demand to implement a secure way of connecting vehicles, as well as verifying and storing their data in a trusted way. Furthermore, much information must be [...] Read more.
The automotive industry currently is seeking to increase remote connectivity to a vehicle, which creates a high demand to implement a secure way of connecting vehicles, as well as verifying and storing their data in a trusted way. Furthermore, much information must be leaked in order to correctly diagnose the vehicle and determine when or how to remotely update it. In this context, we propose a Blockchain-based, fully automated remote vehicle diagnosis system. The proposed system provides a secure and trusted way of storing and verifying vehicle data and analyzing their performance in different environments. Furthermore, we discuss many aspects of the benefits to different parties, such as the vehicle’s owner and manufacturers. Furthermore, a performance evaluation via simulation was performed on the proposed system using MATLAB Simulink to simulate both the vehicles and Blockchain and give a prototype for the system’s structure. In addition, OMNET++ was used to measure the expected system’s storage and throughput given some fixed parameters, such as sending the periodicity and speed. The simulation results showed that the throughput, end-to-end delay, and power consumption increased as the number of vehicles increased. In general, Original Equipment Manufacturers (OEMs) can implement this system by taking into consideration either increasing the storage to add more vehicles or decreasing the sending frequency to allow more vehicles to join. By and large, the proposed system is fully dynamic, and its configuration can be adjusted to satisfy the OEM’s needs since there are no specific constraints while implementing it. Full article
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19 pages, 3051 KiB  
Article
Intrusion Detection System Using Feature Extraction with Machine Learning Algorithms in IoT
by Dhiaa Musleh, Meera Alotaibi, Fahd Alhaidari, Atta Rahman and Rami M. Mohammad
J. Sens. Actuator Netw. 2023, 12(2), 29; https://doi.org/10.3390/jsan12020029 - 29 Mar 2023
Cited by 30 | Viewed by 5116
Abstract
With the continuous increase in Internet of Things (IoT) device usage, more interest has been shown in internet security, specifically focusing on protecting these vulnerable devices from malicious traffic. Such threats are difficult to distinguish, so an advanced intrusion detection system (IDS) is [...] Read more.
With the continuous increase in Internet of Things (IoT) device usage, more interest has been shown in internet security, specifically focusing on protecting these vulnerable devices from malicious traffic. Such threats are difficult to distinguish, so an advanced intrusion detection system (IDS) is becoming necessary. Machine learning (ML) is one of the promising techniques as a smart IDS in different areas, including IoT. However, the input to ML models should be extracted from the IoT environment by feature extraction models, which play a significant role in the detection rate and accuracy. Therefore, this research aims to introduce a study on ML-based IDS in IoT, considering different feature extraction algorithms with several ML models. This study evaluated several feature extractors, including image filters and transfer learning models, such as VGG-16 and DenseNet. Additionally, several machine learning algorithms, including random forest, K-nearest neighbors, SVM, and different stacked models were assessed considering all the explored feature extraction algorithms. The study presented a detailed evaluation of all combined models using the IEEE Dataport dataset. Results showed that VGG-16 combined with stacking resulted in the highest accuracy of 98.3%. Full article
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26 pages, 788 KiB  
Article
Implementation of a Biometric-Based Blockchain System for Preserving Privacy, Security, and Access Control in Healthcare Records
by Ezedin Barka, Mohammed Al Baqari, Chaker Abdelaziz Kerrache and Jorge Herrera-Tapia
J. Sens. Actuator Netw. 2022, 11(4), 85; https://doi.org/10.3390/jsan11040085 - 13 Dec 2022
Cited by 6 | Viewed by 3532
Abstract
The use of Electronic Health Record (EHR) systems has emerged with the continuous advancement of the Internet of Things (IoT) and smart devices. This is driven by the various advantages for both patients and healthcare providers, including timely and distant alerts, continuous control, [...] Read more.
The use of Electronic Health Record (EHR) systems has emerged with the continuous advancement of the Internet of Things (IoT) and smart devices. This is driven by the various advantages for both patients and healthcare providers, including timely and distant alerts, continuous control, and reduced cost, to name a few. However, while providing these advantages, various challenges involving heterogeneity, scalability, and network complexity are still open. Patient security, data privacy, and trust are also among the main challenges that need more research effort. To this end, this paper presents an implementation of a biometric-based blockchain EHR system (BBEHR), a prototype that uniquely identifies patients, enables them to control access to their EHRs, and ensures recoverable access to their EHRs. This approach overcomes the dependency on the private/public key approach used by most blockchain technologies to identify patients, which becomes more crucial in situations where a loss of the private key permanently hinders the ability to access patients’ EHRs. Our solution covers component selection, high-level implementation, and integration of subsystems, was well as the coding of a prototype to validate the mitigation of the risk of permanent loss of access to EHRs by using patients’ fingerprints. A performance analysis of BBEHR showed our system’s robustness and effectiveness in identifying patients and ensuring access control for their EHRs by using blockchain smart contracts with no additional overhead. Full article
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20 pages, 2750 KiB  
Article
IPChain: Blockchain-Based Security Protocol for IoT Address Management Servers in Smart Homes
by Bello Musa Yakubu, Majid Iqbal Khan and Pattarasinee Bhattarakosol
J. Sens. Actuator Netw. 2022, 11(4), 80; https://doi.org/10.3390/jsan11040080 - 24 Nov 2022
Cited by 5 | Viewed by 2682
Abstract
The dynamic host configuration protocol (DHCP) servers are forms of an Internet of Things (IoT) address management server (IoTAMS) that gives network configuration settings to newly connected hosts. Administrators of a network may save time by setting DHCP servers instead of every network [...] Read more.
The dynamic host configuration protocol (DHCP) servers are forms of an Internet of Things (IoT) address management server (IoTAMS) that gives network configuration settings to newly connected hosts. Administrators of a network may save time by setting DHCP servers instead of every network node. However, the absence of a more robust authentication method for DHCP servers makes hosts susceptible to attacks since neither the server nor the users are able to check the other’s authenticity during DHCP connections. These concerns result in both internal and external threats to the system that have the potential to impair network services. Among these threats are malicious DHCP servers and DHCP starvation. This paper aims to provide a novel approach for tackling these issues and protect the DHCP protocol. The proposed model uses the Diffie–Hellman key exchange mechanism, the elliptic curve discrete logarithm problem (ECDLP), a one-way hash function, blockchain technology, and a smart contract. In addition, registration and validation processes provide support for the proposed model in combating DHCP risks for both internal and external system threats. Results from this study show that the proposed model has an average of 21.1% more resistance to a growing number of adversaries than the benchmark models, thus revealing that the model is better suited for the security of IoT address management servers in smart homes, thereby enhancing resilience against related threats and the success of IP address management. Full article
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12 pages, 1102 KiB  
Article
A Blockchain-Based Intrusion Detection System Using Viterbi Algorithm and Indirect Trust for IIoT Systems
by Geetanjali Rathee, Chaker Abdelaziz Kerrache and Mohamed Amine Ferrag
J. Sens. Actuator Netw. 2022, 11(4), 71; https://doi.org/10.3390/jsan11040071 - 27 Oct 2022
Cited by 14 | Viewed by 2637
Abstract
The industrial internet of things (IIoT) is considered a new paradigm in the era of wireless communication for performing automatic communication in the network. However, automatic computation and data recognition may invite several security and privacy threats into the system during the sharing [...] Read more.
The industrial internet of things (IIoT) is considered a new paradigm in the era of wireless communication for performing automatic communication in the network. However, automatic computation and data recognition may invite several security and privacy threats into the system during the sharing of information. There exist several intrusion detection systems (IDS) that have been proposed by several researchers. However, none of them is able to maintain accuracy while identifying the threats and give a high false-positive rate in the network. Further, the existing IDS are not able to recognize the new patterns or anomalies in the network. Therefore, it is necessary to propose a new IDS. The aim of this paper is to propose an IDS using the Viterbi algorithm, indirect trust, and blockchain mechanism for IIoT to ensure the required security levels. The Viterbi algorithm and indirect trust mechanism are used to measure the probability of malicious activities occurring in the network while generating, recording, and shipping products in an IIoT environment. Further, the transparency of the system is maintained by integrating blockchain mechanisms with Viterbi and indirect methods. The proposed framework is validated and analyzed against various security measures by comparing it with the existing approaches. Full article
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23 pages, 1523 KiB  
Article
A Trusted Security Key Management Server in LoRaWAN: Modelling and Analysis
by Koketso Ntshabele, Bassey Isong, Naison Gasela and Adnan M. Abu-Mahfouz
J. Sens. Actuator Netw. 2022, 11(3), 52; https://doi.org/10.3390/jsan11030052 - 5 Sep 2022
Cited by 3 | Viewed by 2272
Abstract
The traditional Long-Range Wide-Area Network (LoRaWAN) uses an Advanced Encryption Standard (AES) 128 bit symmetric key to secure entities and data against several attacks. However, due to the existence of heterogeneous applications, designing a globally accepted and resilient LoRaWAN security model is challenging. [...] Read more.
The traditional Long-Range Wide-Area Network (LoRaWAN) uses an Advanced Encryption Standard (AES) 128 bit symmetric key to secure entities and data against several attacks. However, due to the existence of heterogeneous applications, designing a globally accepted and resilient LoRaWAN security model is challenging. Although several security models to maximize the security efficiency in LoRaWAN exist using the trusted key server to securely manage the keys, designing an optimum LoRaWAN security model is yet to be fully realized. Therefore, in this paper, we proposed two LoRaWAN security algorithms, A and B, for a trusted key management server (TKMS) to securely manage and distribute the keys amongst the entities. Algorithm B is an enhanced version of Algorithm A, which utilizes the security shortcomings of Algorithm A. We employed two formal analysis methods in the modelling, results analysis, and verification. The Scyther security verification tool was used for algorithm modelling and analysis against all possible attacks, while BAN logic was used to prove the logical correctness of the proposed algorithms. The results indicate that BAN logic feasibly proves the model logic correctness and the security claims employed in Scyther are reliable metrics for assessing the algorithms’ security efficiency. The security claims proved that the security algorithm is more secure and reliable as no attacks were detected across all entities in the enhanced-Algorithm B, unlike in Algorithm A. Moreover, the application of hashing minimizes computation cost and time for authentication and message integrity as compared to symmetric and asymmetric encryption. However, the proposed algorithm is yet to be verified as completely lightweight. Full article
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Review

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22 pages, 666 KiB  
Review
A Review of Research on Privacy Protection of Internet of Vehicles Based on Blockchain
by Wendong Chen, Haiqin Wu, Xiao Chen and Jinfu Chen
J. Sens. Actuator Netw. 2022, 11(4), 86; https://doi.org/10.3390/jsan11040086 - 19 Dec 2022
Cited by 6 | Viewed by 3832
Abstract
Numerous academic and industrial fields, such as healthcare, banking, and supply chain management, are rapidly adopting and relying on blockchain technology. It has also been suggested for application in the internet of vehicles (IoV) ecosystem as a way to improve service availability and [...] Read more.
Numerous academic and industrial fields, such as healthcare, banking, and supply chain management, are rapidly adopting and relying on blockchain technology. It has also been suggested for application in the internet of vehicles (IoV) ecosystem as a way to improve service availability and reliability. Blockchain offers decentralized, distributed and tamper-proof solutions that bring innovation to data sharing and management, but do not themselves protect privacy and data confidentiality. Therefore, solutions using blockchain technology must take user privacy concerns into account. This article reviews the proposed solutions that use blockchain technology to provide different vehicle services while overcoming the privacy leakage problem which inherently exists in blockchain and vehicle services. We analyze the key features and attributes of prior schemes and identify their contributions to provide a comprehensive and critical overview. In addition, we highlight prospective future research topics and present research problems. Full article
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