Bezemskij, Anatolij, Loukas, George ORCID: 0000-0003-3559-5182, Anthony, Richard J. and Gan, Diane ORCID: 0000-0002-0920-7572 (2017) Behaviour-based anomaly detection of cyber-physical attacks on a robotic vehicle. In: 2016 15th International Conference on Ubiquitous Computing and Communications and 2016 8th International Symposium on Cyberspace and Security (IUCC-CSS). IEEE, pp. 61-68. ISBN 978-1-5090-5567-8 (doi:https://doi.org/10.1109/IUCC-CSS.2016.017)

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Abstract

Security is one of the key challenges in cyber-physical systems, because by their nature, any cyber attack against them can have physical repercussions. This is a critical issue for autonomous vehicles; if compromised in terms of their communications or computation they can cause considerable physical damage due to their mobility. Our aim here is to facilitate the automatic detection of cyber attacks on a robotic vehicle. For this purpose, we have developed a detection mechanism, which monitors real-time data from a large number of sources onboard the vehicle, including its sensors, networks and processing. Following a learning phase, where the vehicle is trained in a non-attack state on what values are considered normal, it is then subjected to a series of different cyber-physical and physical-cyber attacks. We approach the problem as a binary classification problem of whether the robot is able to self-detect when and whether it is under attack. Our experimental results show that the approach is promising for most attacks that the vehicle is subjected to. We further improve its performance by using weights that accentuate the anomalies that are less common thus improving overall performance of the detection mechanism for unknown attacks.

Item Type:	Conference Proceedings
Title of Proceedings:	2016 15th International Conference on Ubiquitous Computing and Communications and 2016 8th International Symposium on Cyberspace and Security (IUCC-CSS)
Additional Information:	CSS 2016: 8th International Symposium on Cyberspace Safety and Security, December 14th-16th, 2016, Granada, Spain.
Uncontrolled Keywords:	Cyber security, Robotic vehicles, Vehicular security, Intrusion detection, Behaviour-based, Anomaly detection
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Faculty / School / Research Centre / Research Group:	Faculty of Engineering & Science > Internet of Things and Security Research Centre (ISEC) Faculty of Engineering & Science > School of Computing & Mathematical Sciences (CMS) Faculty of Engineering & Science
Related URLs:	Organisation
Last Modified:	04 Mar 2022 13:07
URI:	http://gala.gre.ac.uk/id/eprint/15819

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