Attack Pattern Mining to Discover Hidden Threats to Industrial Control Systems
This work addresses security threats for industrial control systems, but it appears incremental as it focuses on validating a specific technique.
The authors tackled the problem of generating diverse attack patterns for Industrial Control System security by proposing a data-driven technique, which produced over 100,000 patterns from a water treatment plant dataset and was validated through a case study.
This work focuses on validation of attack pattern mining in the context of Industrial Control System (ICS) security. A comprehensive security assessment of an ICS requires generating a large and variety of attack patterns. For this purpose we have proposed a data driven technique to generate attack patterns for an ICS. The proposed technique has been used to generate over 100,000 attack patterns from data gathered from an operational water treatment plant. In this work we present a detailed case study to validate the attack patterns.