Design of a provable secure lightweight privacy-preserving authentication protocol for autonomous vehicles in IoT systems
The rapid advancement of the Internet of Things (IoT) has enabled the adoption of autonomous vehicles (AVs) and drones in intelligent transportation systems (ITS), improving traffic efficiency and safety. However, security and privacy in interconnected ITS environments is a major concern. It is imperative to safeguard sensitive information from various known attacks while enabling secure communication. Keeping in view the security and privacy of autonomous vehicles in IoT systems, this paper puts forward Provable Secure Lightweight Privacy-Preserving Authentication Protocol (PSLAP). The proposed PSLAP protocol achieves high-level security by utilizing cryptographic primitives such as exclusive-OR, secure one-way hash, elliptic curve cryptography (ECC), and concatenation operators. The proposed PSLAP protocol is demonstrated to be resistant to numerous known security assaults through an informal security and privacy assessment. This study presents a formal security analysis using a widely accepted real-or-random (ROR) model which demonstrates the security hardness of the proposed scheme. Additionally, the performance analysis shows that the proposed protocol has minimal computation and communication costs compared to other existing protocols.
Authors
- Norziana Jamil (ORCID: https://orcid.org/0000-0002-7363-1466)
- Ismail Taha Ahmed (ORCID: https://orcid.org/0000-0003-1273-3845)
- Mehedi Masud (ORCID: https://orcid.org/0000-0001-6019-7245)
- Aymen Dia Eddine Berini (ORCID: https://orcid.org/0000-0001-7215-1666)
- Mohd Shariq (ORCID: https://orcid.org/0000-0002-0688-1019)
Institutions
- Abu Dhabi University (AE)
- Al Ain University (AE)
- Taif University (SA)
- United Arab Emirates University (AE)
- University of Anbar (IQ)
Publication Details
- Journal
- Computer Networks
- Published
- 2025-02-28
- DOI
- https://doi.org/10.1016/j.comnet.2025.111155
- Citations
- 15
- Primary Topic
- Advanced Authentication Protocols Security
- Type
- article
- Field-Weighted Citation Impact
- 22.31
Funders
- United Arab Emirates University
- Taif University