D-BLAC: A dual blockchain-based decentralized architecture for authentication and communication in VANET

Tandon, Righa; Verma, Ajay; Gupta, P.K.

doi:10.1016/j.eswa.2023.121461

Cited by 11 publications

(4 citation statements)

References 24 publications

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“…As the safety of automotive passengers and pedestrians has become an issue of paramount concern, there is a large amount of study is being carried out both in industry and academia to address this issue [16], [17]. IDSs, which play a great role in it, are mainly categorized into two categories signature-based and anomaly-based.…”

Section: Intrusion Detection System For Automotivementioning

confidence: 99%

Meta-IDS: Meta-Learning Automotive Intrusion Detection Systems with Adaptive and Learnable

Wang,

Li,

Huang

et al. 2024

Preprint

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In the rapidly evolving landscape of vehicular communications, the widespread use of the Controller Area Network (CAN) in modern vehicles has revealed significant security vulnerabilities. However, existing Intrusion Detection Systems (IDS) struggle to adapt to varied attack scenarios and precisely detect low-volume attacks. In this paper, we introduce a novel IDS that employs meta-learning via the Meta-SGD algorithm, enhancing adaptability across a diverse spectrum of cyber threats, called Meta-IDS. Specifically, our methodology includes a bi-level optimization technique where the inner level focuses on optimizing detection accuracy for specific attack scenarios, and the outer level adjusts meta-parameters to ensure generalizability across different scenarios. For modeling low-volume attacks, we devise the Attack Prominence Score (APS), identifying subtle attack patterns with a threshold of APS \(\textgreater\) 7, allowing for precise differentiation of these attacks. The extensive experiment results show that the proposed method facilitates efficient tuning and rapid adaptation for different modeling paradigms in few-shot scenarios. The detection performance is exceptional, with F1-scores reaching 100% across most attack scenarios, including low-volume attacks. Also, the real-time vehicle-level evaluations demonstrate its adaptability for the vehicular networks.

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Section: Intrusion Detection System For Automotivementioning

confidence: 99%

Meta-IDS: Meta-Learning Automotive Intrusion Detection Systems with Adaptive and Learnable

Wang,

Li,

Huang

et al. 2024

Preprint

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“…In [18], the researchers propose a scheme that they call dual-blockchain-based decentralized architecture for the authentication of nodes as well as secure and efficient communication inside the IoV network. As they claim, the use of individual blockchains for authentication and message sharing lets the network be more efficient and faster, and at the same time helps to raise the security of the network.…”

Section: Blockchain Schemes To Iov Privacy Preservationmentioning

confidence: 99%

Enhancing Privacy in the Internet of Vehicles via Hyperelliptic Curve Cryptography

Routis,

Dagas,

Roussaki

2024

Electronics

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The Internet of Things (IoT) is a technological paradigm that has gained significant momentum the last decade and, among other features, enables the development of intelligent and interoperable device networks. In this respect, it has triggered the creation and evolution of vehicular ad-hoc networks (VANETs), which are initially implemented in order to guarantee the safety of drivers and the avoidance of traffic accidents. The drawback is that this fast evolution comes with serious concerns in terms of the privacy of users, while the population of attackers or entities that try to eavesdrop and intercept information has significantly increased. This imposes a serious risk for drivers moving across a Smart City. The research presented in this paper aims to evaluate privacy protection mechanisms in VANET environments, based on the efficiency and security level they ensure, considering the fact that VANETs provide limited resources to users/drivers. Moreover, the usage of elliptic curve cryptography in reduced resources environments is discussed. Finally, this paper compares the performance of three cryptographic algorithms, elliptic curve cryptography (ECC), hyperelliptic curve cryptography genus 2 (HECC-2) and HECC genus 3 (HECC-3), employed for an efficient authentication and safe message transmission mechanism in VANETs, aimed at reaching conclusions related to the implementation of each cryptographic scheme in this specific application area. The evaluation results indicate that ECC supersedes HECC-2 and HECC-3 in most metrics. However, HECC-2 and HECC-3 demonstrate better responses than ECC does in selected energy metrics. Overall, it is observed that HECC algorithms are not yet mature enough to compete with ECC. This is due to the fact that the research community has not sufficiently progressed toward the optimization of HECC, and moreover, HECC builds on quite complex mathematics. There are indications, however, that once HECC curves are indeed optimized, HECC will outperform ECC in speed as well as in other metrics, sinceHECC-2 and HECC-3 use a significantly smaller key size with the same level of security as that of ECC.

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“…This protocol is adept at mitigating diverse attacks while concurrently reducing the computational overhead and storage footprint associated with authentication messages. Tandon et al [39] introduced a decentralized architecture based on dual blockchains for vehicle authentication and secure, efficient communication within the network. This approach employs separate blockchains for identity verification, message sharing, and enhancing network efficiency, responsiveness, and security.…”

Section: Related Studiesmentioning

confidence: 99%

A Lightweight, Efficient, and Physically Secure Key Agreement Authentication Protocol for Vehicular Networks

Wang,

Fan,

et al. 2024

Electronics

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In the contemporary era, Vehicular Ad Hoc Networks (VANETs) have emerged as a vital technology in intelligent transportation systems, substantially enhancing the overall travel experience by providing advanced services to vehicles while ensuring driver safety. Despite the notable improvements, the inherent complexity of VANETs presents persistent security challenges, encompassing issues such as privacy preservation for vehicles, message authentication, and constraints in computational power and network bandwidth. Various authentication protocols have been designed for VANETs. However, many of these protocols exhibit significant vulnerabilities, rendering them insecure and unreliable in the face of diverse security threats, such as denial of service, replay, forgery, and impersonation attacks. Moreover, some existing schemes encounter limitations, including high computational complexity and the introduction of additional communication overhead and computational costs. To tackle these concerns, we designed a lightweight and secure identity authentication protocol based on elliptic curve cryptography with the objective of furnishing an effective and secure data transmission mechanism across a public communication channel for the Internet of Vehicles. In addition, we introduce Physically Unclonable Functions (PUFs) to ensure physical layer security during the communication process. A detailed security analysis demonstrates that the proposed protocol is resilient against various attacks. Through a comparative analysis with existing relevant protocols, in scenarios with a high density of vehicles, the algorithm demonstrates significantly lower computational costs and communication overhead than the related protocols, indicating that the proposed protocol is lightweight and efficient. Consequently, the empirical findings indicate that our protocol surpasses others in terms of reliability, user convenience, and practicality for ensuring secure data transmission within VANETs.

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D-BLAC: A dual blockchain-based decentralized architecture for authentication and communication in VANET

Cited by 11 publications

References 24 publications

Meta-IDS: Meta-Learning Automotive Intrusion Detection Systems with Adaptive and Learnable

Meta-IDS: Meta-Learning Automotive Intrusion Detection Systems with Adaptive and Learnable

Enhancing Privacy in the Internet of Vehicles via Hyperelliptic Curve Cryptography

A Lightweight, Efficient, and Physically Secure Key Agreement Authentication Protocol for Vehicular Networks

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