Temporal-symbolic data representation for intrusion detection in Industrial Control Systems

This academic paper presents a new method for detecting intrusions (unauthorized access or attacks) in Industrial Control Systems (ICS, which are computers that manage physical infrastructure like power plants or factories) by combining temporal data (information about when events happen) with symbolic data (categorical information like event types). The approach aims to improve security monitoring in critical infrastructure by better identifying suspicious network activity patterns.