A Fog Computing and Blockchain-based Anonymous Authentication Scheme to Enhance Security in VANET Environments
Received: 7 August 2024 | Revised: 26 August 2024 | Accepted: 29 August 2024 | Online: 2 February 2025
Corresponding author: Ali A. Yassin
Abstract
Authentication of vehicles and users, integrity of exchanged messages, and privacy preservation are essential features in VANETs. VANETs are used to collect information on road conditions, vehicle location and speed, and traffic congestion data. The open exchange of information within VANETs poses serious security threats. Furthermore, existing schemes have higher communication and computational costs, making them incompatible with resource-constrained VANET applications. This study proposes a multifactor authentication and privacy-preserving security scheme for VANETs based on blockchain and fog computing to meet all these requirements. The proposed scheme uses fingerprints and Quick Response (QR) codes as a multifactor to authenticate vehicle users and fog-cloud computing techniques to reduce the computational burden on RSUs and improve service quality and resilience. Additionally, the scheme synchronizes a consistent ledger across all RSUs using blockchain technology to store and distribute vehicle authentication statuses. Through a thorough comparison with relevant current protocols, the scheme shows a much-reduced computing expense and communication burden in situations with high vehicle density within a timeframe of 6.3846 ms and 544 bytes for communication costs. In addition, the proposed scheme demonstrates a successful balance between efficacy and complexity, protecting confidentiality, anonymous authentication, and ensuring integrity and conditional tracking. Formal and informal security analysis showed that the proposed scheme is more reliable, practical, and secure against many hostile attacks, such as modification attacks, 51% attacks, Sybil attacks, and MITM attacks.
Keywords:
VANET, blockchain, fog computing, fingerprint, QR code, anonymous authentication, security and privacy, integrityDownloads
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Copyright (c) 2024 Zahraa Sh. Alzaidi, Ali A. Yassin, Zaid Ameen Abduljabbar, Vincent Omollo Nyangaresi
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