A Drone-Assisted Anonymous Authentication and Key Agreement Protocol with Access Control for Accident Rescue in the Internet of Vehicles

Author:

Zheng Jihu1,Duan Haixin1,Wang Chenyu2,Cao Qiang2ORCID,Xu Guoai3,Fang Rui1

Affiliation:

1. Institute for Network Sciences and Cyberspace, Tsinghua University, Beijing 100084, China

2. School of Cyberspace Security, Beijing University of Posts and Telecommunications, Beijing 100876, China

3. School of Computer Science and Technology, Harbin Institute of Technology, Shenzhen 518055, China

Abstract

The drone-assisted Internet of Vehicles (DIoV) displays great potential in the punctual provision of rescue services without geographical limitations. To ensure data security in accident response and rescue services, authentication schemes with access control are employed. These schemes ensure that only specific rescue vehicle operators acting within a valid period can achieve mutual authentication from a designated processor, while access for mismatched, revoked, or expired users is denied. However, the current alternatives fail to ensure session key forward secrecy, entities’ mutual authentication, and user anonymity, thereby compromising users’ privacy and the security of communications. Moreover, executing too many time-consuming operations on vehicles’ resource-constrained devices inevitably degrades the performance of the authentication protocol. Balancing security and performance in the design of an authentication protocol with access control presents a significant challenge. To address this, a more efficient and robust authentication with access control has been designed. The proposed protocol ensures user anonymity through dynamic pseudonym allocation, achieves forward secrecy by excluding the long-term key from session key generation, and obtains mutual authentication by verifying the integrity of the messages exchanged. According to the security and performance analysis, it is demonstrated that the proposal is a robust, efficient, and cost-effective solution. In particular, the proposal can reduce the computational overhead by 66% compared to recent alternatives.

Funder

National Key Research and Development Program of China (Data Security Risk Evolution Mechanism and Security Framework for Vehicle-Road-Cloud Multi-Network Convergence System).

Publisher

MDPI AG

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