Improve Safety and Security of Intelligent Railway Transportation System Based on Balise Using Machine Learning Algorithm and Fuzzy System

With the advancement of modern rail transport systems, high-speed railways' safety and reliability is improved enormously due to proper intelligent traffic management systems. The automatic train control and operating system receive the train location beacons and the railway line's essential information through various channels, such as Balise wirelessly. However, this technology is vulnerable to cyber-physical attacks. This article aims to investigate the existing cyber attacks on Balise that can result a physical turmoil. Due to the limitations and constraints of the railway infrastructures, the attacks and failure detection methods are proposed based on machine learning. Also, a fuzzy countermeasure system is developed to improve train safety against known and unknown cyber-attacks. The simulation results show 92% accuracy in the proposed successful attacks detection system. Moreover, a small amount of false-positive and false-negative warnings can be also revealed employing the proposed scheme. The proposed method does not require change railway infrastructure.