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MARINE: man-in-the-middle attack resistant trust model in connected vehicles

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journal contribution
posted on 2022-03-17, 09:07 authored by Farhan Ahmad, Fatih Kurugollu, Asma AdnaneAsma Adnane, Rasheed Hussain, Fatima Hussain
Vehicular ad hoc network (VANET), a novel technology, holds a paramount importance within the transportation domain due to its abilities to increase traffic efficiency and safety. Connected vehicles propagate sensitive information which must be shared with the neighbors in a secure environment. However, VANET may also include dishonest nodes such as man-in-the-middle (MiTM) attackers aiming to distribute and share malicious content with the vehicles, thus polluting the network with compromised information. In this regard, establishing trust among connected vehicles can increase security as every participating vehicle will generate and propagate authentic, accurate, and trusted content within the network. In this article, we propose a novel trust model, namely, MiTM attack resistance trust model in connected vehicles (MARINE), which identifies dishonest nodes performing MiTM attacks in an efficient way as well as revokes their credentials. Every node running MARINE system first establishes trust for the sender by performing multidimensional plausibility checks. Once the receiver verifies the trustworthiness of the sender, the received data are then evaluated both directly and indirectly. Extensive simulations are carried out to evaluate the performance and accuracy of MARINE rigorously across three MiTM attacker models and the benchmarked trust model. The simulation results show that for a network containing 35% of MiTM attackers, MARINE outperforms the state-of-the-art trust model by 15%, 18%, and 17% improvements in precision, recall, and 'F' -score, respectively.

History

School

  • Science

Department

  • Computer Science

Published in

IEEE Internet of Things Journal

Volume

7

Issue

4

Pages

3310 - 3322

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Version

  • AM (Accepted Manuscript)

Rights holder

© IEEE

Publisher statement

© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Acceptance date

2020-01-06

Publication date

2020-01-17

Copyright date

2020

eISSN

2327-4662

Language

  • en

Depositor

Dr Asma Adnane. Deposit date: 22 February 2022