Temporal assessment of malicious behaviors: application to turnout field data monitoring

2024/05/02 by Sara Abdellaoui, Emil Dumitrescu, Abdellaoui, Sara +5
Computer Science · #Advanced Malware Detection Techniques #Cryptography and Security (cs.CR) #FOS: Computer and information sciences #FOS: Electrical engineering #Information and Cyber Security #Machine Learning (cs.LG) #Network Security and Intrusion Detection #Systems and Control (eess.SY) #electronic engineering #information engineering

paper · pdf · doi:10.48550/arxiv.2405.02346

openalex publication_date 2024/05/02 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

Monitored data collected from railway turnouts are vulnerable to cyberattacks: attackers may either conceal failures or trigger unnecessary maintenance actions. To address this issue, a cyberattack investigation method is proposed based on predictions made from the temporal evolution of the turnout behavior. These predictions are then compared to the field acquired data to detect any discrepancy. This method is illustrated on a collection of real-life data.

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