Security provision for protecting intelligent sensors and zero touch devices by using blockchain method for the smart cities

Nisa, Khaleeq Un; Alhudhaif, Adi; Qureshi, Kashif Naseer; Hadi, Hassan Jalil; Jeon, Gwanggil

doi:10.1016/j.micpro.2022.104503

Cited by 9 publications

(5 citation statements)

References 12 publications

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“…However, detecting intrusion with standalone ML-or DL-based IDS is challenging as most of the ZTNs applications have longer sequences of time-series data, and also have a large number of features (due to their nonlinear, and nonstationary characteristics) with multiple layers. Few works presented such as in [8] either used blockchain for storing entire transactions or just surveyed generic ways to include blockchain in ZTNs. Furthermore, storing entire transactions on blockchain has proved to be quite inefficient and costly.…”

Section: A Motivation Of Blockchain and Deep Learningmentioning

confidence: 99%

“…As a result, throughput does not expand as the network grows larger and storing entire transactions on blockchain opens scalability issues. Therefore, due to limited storage and computational power, the number of transactions to be added in blockchain must be reduced.Various decentralized storage systems such as IPFS or Swarm, can be used to solve scalability issues, but these platforms can be compromised as data are stored and available to the public [8], [10]. Moreover, current blockchain schemes face interoperability challenges due to the lack of standard and the diverse nature of consensus and blockchain platforms, which create significant communication limitations.…”

Section: Scalability and Interoperabilitymentioning

confidence: 99%

“…However, the majority of contemporary security threats are linked to the growing number of IoT devices and the usage of cloud-based, and edge-based services in ZTNs. For example, IoT devices can easily be compromised by an attacker as they are physically deployed in ZTNs without any security measures [8]. Moreover, several security and privacy breaches are possible in the network as the communication takes place through an insecure channel [9].…”

Section: Introductionmentioning

confidence: 99%

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Deep-Learning-Based Blockchain for Secure Zero Touch Networks

Kumar

Aloqaily

et al. 2023

IEEE Commun. Mag.

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The recent technological advancements in wireless communication systems and Internet of Things (IoT) has accelerated the development of Zero Touch Networks (ZTNs). ZTNs provide self-monitoring, self-configuring, and automated servicelevel policies that cannot be fulfilled by the traditional network Management and Orchestration (MANO) approaches. Despite the hype, the majority of data exchange between participating entities occurs over insecure public channels, which present a number of possible security risks and attacks. Toward this end, we first analyze the attack surface on IoT-enabled ZTNs and the inherent architectural flaws for such threats. After an overview of attack surface, this article presents a new deep learning and blockchain-assisted case study for secure data sharing in ZTNs. Specifically, first, we design a novel Variational AutoEncoder (VAE) and Attention-based Gated Recurrent Units (AGRU)based Intrusion Detection System (IDS) for ZTNs. Second, a novel authentication protocol that combines blockchain, Smart Contracts (SC), Elliptic Curve Cryptography (ECC), and Proofof-Authority (PoA) consensus mechanism is developed to improve secure data sharing in ZTNs. The extensive experimental results show the effectiveness of the proposed approach. Lastly, this work discusses critical issues, opportunities, and open research directions to solve these challenges.

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Section: A Motivation Of Blockchain and Deep Learningmentioning

confidence: 99%

Section: Scalability and Interoperabilitymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Deep-Learning-Based Blockchain for Secure Zero Touch Networks

Kumar

Aloqaily

et al. 2023

IEEE Commun. Mag.

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“…Intelligent software has greatly facilitated our lives. 1 Cyber-Physical Systems (CPS) is a computer system controlled or monitored by computer-based algorithms. In Cyber-Physical Systems, there is a close connection between the physical and the software, which can work on different temporal and spatial scales, exhibit different patterns of behavior, and interact in various ways.…”

Section: Introductionmentioning

confidence: 99%

“…With the rapid development of technologies such as the Internet of Things (IoT), artificial intelligence, and blockchain, a solid foundation has been laid for the development of smart cities, Industry 4.0, and smart agriculture. Intelligent software has greatly facilitated our lives 1 . Cyber‐Physical Systems (CPS) is a computer system controlled or monitored by computer‐based algorithms.…”

Section: Introductionmentioning

confidence: 99%

AI‐enabled blockchain and SDN‐integrated IoT security architecture for cyber‐physical systems

Wang¹,

Zhang²,

Zhang³

2023

Adv Control Appl

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To address the IoT security problem, in this paper we propose and evaluate the DDoS attack mitigation method based on blockchain, and construct a DDoS abnormal information detection and sharing model. The obtained experimental results show that when the number of decision trees increases, the training time of the DDoS attack detection model based on the RF model grows with a minimum trend of 14 s. The testing time is finally maintained at 1 s, and the recognition accuracy of DDoS attacks keeps improving, ultimately reaching over 99.8%. If the amount of DDoS abnormal traffic information exceeds 100 pieces and 2000 pieces, it only takes 0.1 and 5 s to sign the DDoS abnormal traffic information using ECDSA algorithm digitally. The signature verification only takes 0.1 and 9 s, respectively. And compared to conventional network physical system IoT security architecture, a network physical system IoT security architecture that integrates AI empowerment, blockchain, and SDN integration has a higher joint defense success rate. It can be explained that this scheme will be conducive to promoting joint defense against DDoS attacks and ensuring the security of the Internet of Things.

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Exploring security and privacy enhancement technologies in the Internet of Things: A comprehensive review

Ataullah,

Chauhan

2024

Security and Privacy

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In the era heavily influenced by Internet of Things (IoT), prioritizing strong security and the protection of user privacy is of utmost importance. This comprehensive review paper embarks on a meticulous examination of the multifaceted challenges and risks facing IoT security and privacy. It encompasses the hardware, software, and data‐in‐transit domains, shedding light on potential vulnerabilities and associated threats. In response to these concerns, this paper puts forth recommendations for effective strategies to mitigate these risks. Providing a road‐map for enhancing security and privacy in IoT environments. Furthermore, this review thoroughly assesses a multitude of solutions proposed by various authors, with the primary aim of enhancing security and privacy within the IoT landscape. The analysis provides insights into the strengths and limitations of these solutions. This is aiding in the development of a holistic comprehension of the existing status of IoT security and privacy. Moreover, the paper delves into the complexities surrounding integrating emerging technologies into the IoT framework. It explores the obstacles and challenges inherent in this process and proposes potential strategies to address these hurdles. By doing so, the review provides a holistic perspective on existing security and privacy enhancement technologies and offers guidance on navigating the dynamic landscape of emerging technologies within the IoT domain. Publications included in the review consist of journal articles, conference papers, and book chapters from reputable sources indexed in SCI (Science Citation Index), Scopus, and Web of Science.

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Security provision for protecting intelligent sensors and zero touch devices by using blockchain method for the smart cities

Cited by 9 publications

References 12 publications

Deep-Learning-Based Blockchain for Secure Zero Touch Networks

Deep-Learning-Based Blockchain for Secure Zero Touch Networks

AI‐enabled blockchain and SDN‐integrated IoT security architecture for cyber‐physical systems

Exploring security and privacy enhancement technologies in the Internet of Things: A comprehensive review

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