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An Energy-Efficient, Conditional Privacy-Preserving, and Blockchain-Assisted CLAS Scheme for VANETs With Immediate Revocation

Oct 2026 · IEEE Internet of Things Journal · Vol 13, pp. 44853-44867 · 0 citations · 63 references

Abstract

The rapid growth of IoT-enabled intelligent transport systems (ITSs) has made vehicular ad hoc networks (VANETs) a key component for secure and efficient vehicular communication. However, existing signature and authentication schemes for VANETs face several challenges, including high computation and communication overhead, ineffective or delayed revocation of malicious vehicles, vehicle privacy, security vulnerability, and the need to quickly validate pseudo-identity while avoiding single-point failure. To address these issues, this article presents an energy-efficient, privacy-preserving, blockchain-based certificateless aggregate signature (CLAS) scheme for VANETs. The proposed scheme combines a smart contract framework with five functions, namely ViewV, AuthV, TraceV, SubmitV, and RevokeV, to support vehicle registration, authentication, tracing, and revocation. Our scheme detects malicious vehicles before and after blockchain entry, enabling dual-stage malicious vehicle detection, and is also able to revoke malicious vehicles that were honest before blockchain entry but later became malicious. The scheme uses only two bilinear pairings in the aggregate signature verification process and saves computation cost. Unlike traditional schemes, our scheme uses a unique approach where the smart contract identity is transmitted instead of the public key and identity of vehicle, which significantly reduces the signature communication cost. Formal security analysis has shown the scheme to be existentially unforgeable against Type I and Type II adversaries, without using the forking lemma. Blockchain simulations in the Remix VM (Cancun) environment and performance analysis results demonstrate the efficiency of our scheme, with lower CPU power consumption and enhanced RSU service capacity compared to state-of-the-art works.

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