Abstract
Communication-based train control (CBTC) is considered as the main organ of urban rail transit systems, which is facing increasingly serious security threats. Intrusion detection systems (IDS) are crucial for security protection. This paper reports the design principles and evaluation results of a novel hybrid intrusion detection system which is suitable for CBTC systems. This hybrid method combines the advantages of the high true positive rate of network-based IDS (NIDS) and the ability of host-based IDS (HIDS) to monitor system behavior, where decision tree and critical state analysis are used, respectively. The proposed method is verified on a semi-physical simulation platform of CBTC and the experiments show that the designed scheme can detect intrusions accurately with a 97.8% detection rate.
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Acknowledgements
This paper was supported by grants from the National Natural Science Foundation of China (No. 61603031), Beijing Natural Science Foundation (No. L181004), and projects (No. I19L00090), State Key Laboratory of Traffic Control and Safety of Beijing Jiaotong University, and projects (No. I18JB00110), and Beijing Laboratory for Urban Mass Transit.
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Song, Y., Bu, B., Yang, X. (2020). Hybrid Intrusion Detection with Decision Tree and Critical State Analysis for CBTC. In: Liu, B., Jia, L., Qin, Y., Liu, Z., Diao, L., An, M. (eds) Proceedings of the 4th International Conference on Electrical and Information Technologies for Rail Transportation (EITRT) 2019. EITRT 2019. Lecture Notes in Electrical Engineering, vol 640. Springer, Singapore. https://doi.org/10.1007/978-981-15-2914-6_16
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DOI: https://doi.org/10.1007/978-981-15-2914-6_16
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