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

arXiv:2405.02346v1 Announce Type: new
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.

actions address application arxiv assessment attackers conceal cs.cr cs.lg cs.sy cyberattack cyberattacks data eess.sy evolution failures investigation issue maintenance malicious may monitoring predictions railway temporal trigger vulnerable