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Reducing computational cost in IoT cyber security: case study of artificial immune system algorithm. (2019)
Conference Proceeding
ZAKARIYYA, I., AL-KADRI, M.O., KALUTARGE, H. and PETROVSKI, A. 2019. Reducing computational cost in IoT cyber security: case study of artificial immune system algorithm. In Obaidat, M. and Samarati, P. (eds.) Proceedings of the 16th International security and cryptography conference (SECRYPT 2019), co-located with the 16th International joint conference on e-business and telecommunications (ICETE 2019), 26-28 July 2019, Prague, Czech Republic. Setúbal, Portugal: SciTePress [online], 2, pages 523-528. Available from: https://doi.org/10.5220/0008119205230528.

Using Machine Learning (ML) for Internet of Things (IoT) security monitoring is a challenge. This is due to their resource constraint nature that limits the deployment of resource-hungry monitoring algorithms. Therefore, the aim of this paper is to i... Read More about Reducing computational cost in IoT cyber security: case study of artificial immune system algorithm..

Context-aware anomaly detector for monitoring cyber attacks on automotive CAN bus. (2019)
Conference Proceeding
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

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... Read More about Context-aware anomaly detector for monitoring cyber attacks on automotive CAN bus..