Efficient Certificateless Conditional Privacy- Preserving Authentication Scheme With Dynamic Pseudonyms for VANETs
Vehicular Ad hoc Networks (VANETs) are essential technology in intelligent transportation systems, enhancing traffic safety and improving traffic flow management. However, the increasing transmission of sensitive data raises serious security and privacy concerns. Existing certificateless aggregate signature (CLAS)-based authentication schemes face the following limitations in addressing these challenges: First, the complex construction leads to high computational overhead. Second, some schemes have security vulnerabilities and overlook physical-layer protection. Third, pseudonyms are tied to the key generated by trusted authority (TA) in a one-to-one relationship. To address these issues, we propose an efficient identity authentication scheme with conditional privacy-preserving, named ECPAS. By restructuring the existing CLAS scheme and utilizing pairing-free operations to achieve efficiency in computation. Also, ECPAS allows vehicles to cooperate with TA in generating dynamic pseudonyms and key pairs, avoiding key escrow and enhancing privacy. Moreover, the pseudonym of vehicle is generated by biometric identity and two hash seeds, so that the computation and storage overhead can be reduced efficiently under the condition that security is guaranteed. We performed formal and informal analysis that shows ECPAS satisfies the security requirements of VANETs. Finally, experimental results show that ECPAS outperforms existing schemes in computational cost, communication overhead, and transmission delay, and NS3-based simulations further validate its practicality and scalability.
Authors
- Yepeng Guan (ORCID: https://orcid.org/0000-0003-1854-1430)
- S. Chen
Institutions
- Shanghai University (CN)
Publication Details
- Journal
- IEEE Sensors Journal
- Published
- 2025-05-26
- DOI
- https://doi.org/10.1109/jsen.2025.3571740
- Citations
- 2
- Primary Topic
- Vehicular Ad Hoc Networks (VANETs)
- Type
- article
- Field-Weighted Citation Impact
- 1.46
Funders
- National Key Research and Development Program of China