Lightweight Certificateless Authentication Scheme With Enhanced Privacy for CAVs
Connected Autonomous Vehicles (CAVs) represent a transformative advancement in transportation, offering enhanced safety, improved traffic efficiency, and reduced environmental impact through intelligent driving. As CAVs operate without human intervention, they heavily rely on secure vehicle-to-vehicle (V2V) communication for cooperative perception and coordinated decision-making. These real-time inter-vehicle exchanges underpin safe coordination, dynamic decision-making, and collision avoidance. To ensure trust in such communication, robust and efficient authentication mechanisms are essential. However, existing schemes often fall short in terms of security resilience and operational practicality. In this paper, we propose a novel Certificateless Signature Scheme with Conditional Privacy-Preserving Authentication (CLSS-CPPA) tailored to CAV environments. The proposed scheme addresses three fundamental limitations in existing schemes: signature forgery vulnerabilities, single-authority dependency, and lack of dynamic revocation capability. Our approach employs distributed key generation to prevent signature forgery attacks, utilizes prefix tree structures for efficient dynamic key revocation, and implements dual-agency pseudonym management with mutual authority constraints to prevent single-entity power abuse. Lightweight cryptographic operations are also adopted to suit resource-constrained vehicular systems. Formal security analysis and extensive evaluations demonstrate that CLSS-CPPA enhances privacy preserving and reduces signing and verifying costs by 20%–90% compared to state-of-the-art schemes, making it a promising solution for real-world CAV deployments.
Authors
- Ying Dong
- Jelena Mišić (ORCID: https://orcid.org/0000-0002-1251-3730)
- Vojislav B. Mišić (ORCID: https://orcid.org/0000-0001-7760-9920)
- Xiaolin Chang (ORCID: https://orcid.org/0000-0002-2975-8857)
- Yingying Yao (ORCID: https://orcid.org/0000-0003-2553-9259)
Institutions
- Beijing Jiaotong University (CN)
- Toronto Metropolitan University (CA)
Publication Details
- Journal
- IEEE Internet of Things Journal
- Published
- 2025-09-22
- DOI
- https://doi.org/10.1109/jiot.2025.3612990
- Primary Topic
- Advanced Manufacturing and Logistics Optimization
- Type
- article
- Field-Weighted Citation Impact
- 0.00