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Resistance to Cybersecurity Attacks in a Novel Network for Autonomous Vehicles

Brocklehurst, Callum; Radenkovic, Milena

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Authors

Callum Brocklehurst



Abstract

The increased interest in autonomous vehicles has led to the development of novel networking protocols in VANETS. In such a widespread safety critical application, security is paramount to the implementation of the networks. We view new autonomous vehicle edge networks as oppor-tunistic networks that bridge the gap between fully distributed vehicular networks based on short range vehicle to vehicle communication and cellular based infrastructure for centralized solutions. Experiments are conducted using opportunistic networking protocols to provide data to autono-mous trams and buses in a smart city. Attacking vehicles enter the city aiming to disrupt the net-work to cause harm to the general public. In the experiments the number of vehicles and the at-tack length is altered to investigate the impact on the network and vehicles. Considering different measures of success as well as computation expense, measurements are taken from all nodes in the network across different lengths of attack. The data gathered from each node allows explora-tion into how different attacks impact metrics including the delivery probability of a message, the time taken to deliver and the computation expense to each node. The novel multidimensional analysis including geospatial elements provides evidence that the state-of-the-art MaxProp algo-rithm outperforms the benchmark as well as other, more complex routing protocols in most of the categories. Upon the introduction of attacking nodes however, PRoPHET provides the most relia-ble delivery probability while under attack. Two different attack methods (black and grey holes) are used to disrupt the flow of messages throughout the network and the more basic protocols show they are less consistent. In some metrics, the PRoPHET algorithm performs better while un-der attack due to the benefit of reduced network traffic.

Journal Article Type Article
Acceptance Date Jul 11, 2022
Online Publication Date Jul 13, 2022
Publication Date Jul 13, 2022
Deposit Date Jul 11, 2022
Publicly Available Date Jul 13, 2022
Journal Journal of Sensor and Actuator Networks
Electronic ISSN 2224-2708
Peer Reviewed Peer Reviewed
Volume 11
Issue 3
Article Number 35
DOI https://doi.org/10.3390/jsan11030035
Keywords VANETS; Opportunistic Networks; Security
Public URL https://nottingham-repository.worktribe.com/output/8947183
Publisher URL https://www.mdpi.com/2224-2708/11/3/35

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