Resistance to Cybersecurity Attacks in a Novel Network for Autonomous Vehicles

Brocklehurst, Callum; Radenkovic, Milena

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.

Citation

Brocklehurst, C., & Radenkovic, M. (2022). Resistance to Cybersecurity Attacks in a Novel Network for Autonomous Vehicles. Journal of Sensor and Actuator Networks, 11(3), Article 35. https://doi.org/10.3390/jsan11030035

• 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
• Publisher: MDPI
• 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