Vehicular ad hoc networks verification scheme based on bilinear pairings and networks reverse fuzzy extraction

Vehicular Ad-Hoc Networks (VANETs) have facilitated the massive exchange of real-time traffic and weather conditions, which have helped prevent collisions, reduce accidents, and road congestions. This can effectively enhance driving safety and efficiency in technology-driven transportation systems. However, the transmission of massive and sensitive information across public wireless communication channels exposes the transmitted data to a myriad of privacy as well as security threats. Although past researches has developed many vehicular ad-hoc networks security preservation schemes, several of them are inefficient or susceptible to attacks. This work, introduces an approach that leverages reverse fuzzy extraction, bilinear pairing, and Physically Unclonable Function (PUF) to design an efficient and anonymity-preserving authentication scheme. We conduct an elaborate formal security analysis to demonstrate that the derived session key is secure. The semantic security analyses also demonstrate its resilience against typical VANET attacks such as impersonations, denial of service, and de-synchronization, instilling confidence in its effectiveness. Moreover, our approach incurs the lowest computational overheads at relatively low communication costs. Specifically, our protocol attains a 66.696% reduction in computation costs, and a 70% increment in the supported security functionalities.

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Publication Details

Journal
Scientific Reports
Published
2025-08-09
DOI
https://doi.org/10.1038/s41598-025-15011-x
Citations
4
Primary Topic
User Authentication and Security Systems
Type
article
Field-Weighted Citation Impact
12.98
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article

Vehicular ad hoc networks verification scheme based on bilinear pairings and networks reverse fuzzy extraction

Mohammed Abdulridha Hussain, Ali Hasan Ali, Mustafa A. Al Sibahee, Abdulla J. Y. Aldarwish et al.
4 citations
Scientific Reports
User Authentication and Security Systems
12.98
article

Vehicular ad hoc networks verification scheme based on bilinear pairings and networks reverse fuzzy extraction

Mohammed Abdulridha Hussain, Ali Hasan Ali, Mustafa A. Al Sibahee, Abdulla J. Y. Aldarwish, Junchao Ma, Zaid Ameen Abduljabbar, Husam A. Neamah, Ahmed Ali Ahmed, Zaid Alaa Hussien
article en
4 citations

Abstract

Vehicular Ad-Hoc Networks (VANETs) have facilitated the massive exchange of real-time traffic and weather conditions, which have helped prevent collisions, reduce accidents, and road congestions. This can effectively enhance driving safety and efficiency in technology-driven transportation systems. However, the transmission of massive and sensitive information across public wireless communication channels exposes the transmitted data to a myriad of privacy as well as security threats. Although past researches has developed many vehicular ad-hoc networks security preservation schemes, several of them are inefficient or susceptible to attacks. This work, introduces an approach that leverages reverse fuzzy extraction, bilinear pairing, and Physically Unclonable Function (PUF) to design an efficient and anonymity-preserving authentication scheme. We conduct an elaborate formal security analysis to demonstrate that the derived session key is secure. The semantic security analyses also demonstrate its resilience against typical VANET attacks such as impersonations, denial of service, and de-synchronization, instilling confidence in its effectiveness. Moreover, our approach incurs the lowest computational overheads at relatively low communication costs. Specifically, our protocol attains a 66.696% reduction in computation costs, and a 70% increment in the supported security functionalities.

Scientific ReportsVol. 15(1)
University of Basrah (IQ), University of Debrecen (HU), Shenzhen University (CN), Thi Qar University (IQ), Jaramogi Oginga Odinga University of Science and Technology (KE), Al-Balqa Applied University (JO), Southern Technical University (IQ), Shenzhen Technology University (CN), Al-Ayen Iraqi University (IQ), Saveetha University (IN)
Sustainable cities and communities
Openalex Percentile: Top 2%
User Authentication and Security Systems
12.98
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