A comparative analysis of multi‐criteria decision methods for secure beacon selection in vehicular platoons

Sean Joe Taylor, Farhan Ahmad, Hoang Nga Nguyen, Siraj Ahmed Shaikh, Jeremy Bryans, Charles E. Wartnaby

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Vehicle platoons are a novel transportation technology which not only aims to ensure traffic safety but also create a positive impact on the environment by producing low CO2 emissions. Vehicle platoons rely heavily on wireless communication to ensure that vehicles (leader and members) moving at high speed can keep close formation by exchanging beacons containing significant, authentic and accurate information. However, the presence of malicious attackers launching different attacks such as false data injection (FDI) can compromise the security of vehicle platoons by tampering with the beacons. Therefore, to avoid FDI attacks, we relied on multi‐criteria decision methods (MCDM)‐based methods in order to select the optimum beacon to share authentic and accurate information with the member vehicles. In this study, three MCDM methods including weighted sum model, technique for order of preference by similarity to ideal solution and preference ranking organization method for enrichment of evaluations (PROMETHEE‐II) are studied and compared with the aim to enable the platoons to select the optimum beacon for communication. We performed extensive simulations to evaluate the performance of these methods in the presence of three FDI attacker models from four different aspects, that is, safety, stability, environmental, and cyber security. Our results demonstrate that MCDM‐based methods can increase network efficiency, but at the cost of a trade‐off between safety and cyber security.
Original languageEnglish
Article numbere4841
Pages (from-to)(In-Press)
Number of pages20
JournalTransactions on Emerging Telecommunications Technologies
Early online date8 Aug 2023
Publication statusE-pub ahead of print - 8 Aug 2023

Bibliographical note

This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.


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