A Novel Intrusion Detection Model Using a Fusion of Network and Device States for Communication-Based Train Control Systems

Author:

Song YajieORCID,Bu BingORCID,Zhu Li

Abstract

Security is crucial in cyber-physical systems (CPS). As a typical CPS, the communication-based train control (CBTC) system is facing increasingly serious cyber-attacks. Intrusion detection systems (IDSs) are vital to protect the system against cyber-attacks. The traditional IDS cannot distinguish between cyber-attacks and system faults. Furthermore, the design of the traditional IDS does not take the principles of CBTC systems into consideration. When deployed, it cannot effectively detect cyber-attacks against CBTC systems. In this paper, we propose a novel intrusion detection method that considers both the status of the networks and those of the equipment to identify if the abnormality is caused by cyber-attacks or by system faults. The proposed method is verified on a hardware-in-the-loop simulation platform of CBTC systems. Simulation results indicate that the proposed method has achieved 97.64% true positive rate, which can significantly improve the security protection level of CBTC systems.

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Hardware and Architecture,Signal Processing,Control and Systems Engineering

Cited by 11 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Open DGML: Intrusion Detection Based on Open-Domain Generation Meta-Learning;Applied Sciences;2024-06-22

2. A transfer learning-based intrusion detection system for zero-day attack in communication-based train control system;Cluster Computing;2024-04-12

3. Conditional Generative Adversarial Network for Intrusion Detection System Based on Deep Learning;2024 16th International Conference on Computer and Automation Engineering (ICCAE);2024-03-14

4. Accuracy Enhancement for Intrusion Detection Systems Using LSTM Approach;Lecture Notes in Networks and Systems;2024

5. CBTCset: A Reference Dataset for Detecting Misbehavior Attacks in CBTC Networks;2023 IEEE 34th International Symposium on Software Reliability Engineering Workshops (ISSREW);2023-10-09

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