Dr Harsha Kalutarage h.kalutarage@rgu.ac.uk
Senior Lecturer
Context-aware anomaly detector for monitoring cyber attacks on automotive CAN bus.
Kalutarage, Harsha Kumara; Al-Kadri, M. Omar; Cheah, Madeline; Madzudzo, Garikayi
Authors
M. Omar Al-Kadri
Madeline Cheah
Garikayi Madzudzo
Contributors
Hans-Joachim Hof
Editor
Mario Fritz
Editor
Christoph Kraub
Editor
Oliver Wasenm�ller
Editor
Abstract
Automotive electronics is rapidly expanding. An average vehicle contains million lines of software codes, running on 100 of electronic control units (ECUs), in supporting number of safety, driver assistance and infotainment functions. These ECUs are networked using a Controller Area Network (CAN). Security of the CAN bus has not historically been a major concern, however, recent research demonstrate that CAN has many vulnerabilities to cyber attacks. This paper presents a contextualised anomaly detector for monitoring cyber attacks on the CAN bus. Proposed algorithm is based on message sequence modelling, using so called N-grams distributions. It utilises only benign data (one class) for training and threshold estimation. Performance of the algorithm was tested against two different attack scenarios, RPM and gear gauge messages spoofing, using data captured from a real vehicle. Experimental outcomes demonstrate that proposed algorithm is capable of detecting both attacks with 100% accuracy, using far smaller time windows (100ms) which is essential for a practically deployable automotive cyber security solution.
Citation
KALUTARAGE, H.K., AL-KADRI, M.O., CHEAH, M. and MADZUDZO, G. 2019. Context-aware anomaly detector for monitoring cyber attacks on automotive CAN bus. In Hof, H.-J., Fritz, M., Kraub, C. and Wasenmüller, O. (eds.). Proceedings of 2019 Computer science in cars symposium (CSCS 2019), 8 October 2019, Kaiserslautern, Germany. New York: ACM [online], article number 7. Available from: https://doi.org/10.1145/3359999.3360496
Conference Name | 2019 Computer science in cars symposium (CSCS 2019) |
---|---|
Conference Location | Kaiserslautern, Germany |
Start Date | Oct 8, 2019 |
Acceptance Date | Sep 11, 2019 |
Online Publication Date | Oct 8, 2019 |
Publication Date | Oct 8, 2019 |
Deposit Date | Sep 12, 2019 |
Publicly Available Date | Mar 29, 2024 |
Publisher | Association for Computing Machinery (ACM) |
ISBN | 9781450370042 |
DOI | https://doi.org/10.1145/3359999.3360496 |
Keywords | In-vehicle networks; CAN bus; Automotive cyber security; Context-aware anomaly detection |
Public URL | https://rgu-repository.worktribe.com/output/544552 |
Files
KALUTARAGE 2019 Context aware anomaly
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Publisher Licence URL
https://creativecommons.org/licenses/by-nc/4.0/
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