Review of Network Anomaly Detection in the High-speed Railway Signal System Based on Artificial Intelligence

Abstract

The advent of network communication technology and associated equipment has significantly enhanced the operation efficiency and automation of the high-speed railway signal system. However, these open and complex networks also face increased security threats. To mitigate the risk of malicious network attacks, effective network anomaly detection methods are progressively being adopted. Artificial intelligence (AI), with its exceptional self-learning, environmental adaptability, and massive data processing capabilities, has emerged as the development trend for network anomaly detection in the high-speed railway signal system. This paper first provides an overview of the current state of network security in the high-speed railway signal system and examines potential network security threats. It then offers a detailed comparison of AI-based network anomaly detection methods. Lastly, it discusses future research directions in this field.