ARISTOTLE: AddRessIng falSe daTa injectiOn atTacks in vehicLE platoons

S. J. Taylor, F. Ahamad, H. N. Nguyen, S. A. Shaikh, D. Evans, C. E. Wartnaby

Research output: Contribution to journalConference articlepeer-review

1 Citation (Scopus)

Abstract

Vehicle platoons are an emerging transportation technology which aims to increase traffic efficiency and safety by enabling high speed vehicles to travel in close formations. Vehicle platoons rely heavily on wireless communication to ensure that vehicles (leader and members) can keep formation by exchanging 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 information. To this end, we propose ARISTOTLE, which has the ability to detect and revoke FDI attacks in vehicle platoons. ARISTOTLE uses a weighted sum model, which is a traditional Multi-Attribute Decision Method. ARISTOTLE operates in two stages where first it predicts the beacon content, and in the next stage, it selects the best beacon to be shared with platoon members. Extensive simulations were carried out to evaluate the performance of ARISTOTLE from safety, stability and environmental aspects. Our results demonstrate that ARISTOTLE can accurately detect FDI attacks and significantly reduce their impact.

Original languageEnglish
Pages (from-to)198-203
Number of pages6
JournalIET Conference Proceedings
Volume2022
Issue number26
DOIs
Publication statusE-pub ahead of print - 23 Feb 2023
Event6th IET Smart Cities Symposium 2022 - Hybrid, Bahrain
Duration: 6 Dec 20228 Dec 2022
https://localevents.theiet.org/register.php?event=441fce

Bibliographical note

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© 2022 IET Conference Proceedings. All rights reserved.

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