A Threat Hunting Framework for Industrial Control Systems

An Industrial Control System (ICS) adversary often takes different actions to exploit vulnerabilities, pass the border between Information Technology (IT) and Operational Technology (OT) networks, and launch a targeted attack against OT networks. Detecting these threat actions in early phases before the final stage of the attacks can be executed against industrial endpoints can help prevent adversaries from achieving their goals. Threat hunting in IT networks has been previously studied, and several hunting methods have been proposed. However, these methods are not sufficient for ICSs, as the integration of industrial legacy systems with advanced IT networks has introduced new types of vulnerabilities and changed the behaviour of attacks. The lack of a unified hunting solution for integrated IT and OT networks is the gap that is considered in our paper. The contribution of this paper is an ICS Threat Hunting Framework (ICS-THF) which focuses on detecting cyber threats against ICS devices in the earliest phases of the attack lifecycle. ICS-THF consists of three stages, threat hunting triggers, threat hunting, and cyber threat intelligence. The threat hunting trigger stage identifies events or external resources that can trigger the hunting stage. The hunting stage uses a combination of the MITRE ATTCK Matrix and a Diamond model of intrusion analysis to generate a hunting hypothesis and to predict the future behaviour of the adversary. This hypothesis will be validated by analysing Diamond models of threat actions. Finally, the cyber threat intelligence stage is responsible for generating Indicators of Compromise (IoCs) to be used for future threat hunting. The Black Energy 3 malware, PLC-Blaster malware, and SWaT dataset are used in this paper to evaluate the efficiency of the proposed framework.