Year: 2025
Type: article
Abstract: The development of Vehicle AD Hoc Networks (VANETs) has significantly enhanced the efficiency of intelligent transportation systems. Through real-time communication between vehicles and roadside units (RSUs), the immediate sharing of traffic information has been achieved. However, challenges such as network congestion, data privacy, and low computing efficiency still exist. Data privacy is at risk of leakage due to the sensitivity of vehicle information, especially in a resource-constrained vehicle environment, where computing efficiency becomes a bottleneck restricting the development of VANETs. To address these challenges, this paper proposes a certificateless aggregated signcryption scheme based on edge computing. This scheme integrates online/offline encryption (OOE) technology and a pseudonym mechanism. It not only solves the problem of key escrow, generating part of the private key through collaboration between the user and the Key Generation Center (KGC), but also uses pseudonyms to protect the real identities of the vehicle and RSU, effectively preventing privacy leakage. This scheme eliminates bilinear pairing operations, significantly improves efficiency, and supports conditional traceability and revocation of malicious vehicles while maintaining anonymity. The completeness analysis shows that under the assumptions of calculating the Diffie–Hellman (CDH) and elliptic curve discrete logarithm problem (ECDLP), this scheme can meet the requirements of IND-CCA2 confidentiality and EUF-CMA non-forgeability. The performance evaluation further confirmed that, compared with the existing schemes, this scheme performed well in both computing and communication costs and was highly suitable for the resource-constrained VANET environment.
Source: Electronics
Authors: Wenfeng Zou, Qiang Guo, Xiaolan Xie
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,896
Award: G5905189938
OpenAlex ID: W4410375201
