On Process Awareness in Detecting Multi-stage Cyberattacks in Smart Grids

TL;DR

This paper investigates how process-aware intrusion detection systems improve detection of complex multi-stage cyberattacks in Smart Grids by leveraging co-simulation environments and machine learning, highlighting the importance of operational process context.

Contribution

It introduces the use of process awareness in IDS for Smart Grids and demonstrates its effectiveness over traditional IT-only approaches in detecting sophisticated cyber threats.

Findings

Process-aware IDS outperform IT-only IDS in detection accuracy.

Operational process context enhances detection of complex cyberattacks.

Development of advanced IDS benchmarks and digital twin datasets is crucial.

Abstract

This study delves into the role of process awareness in enhancing intrusion detection within Smart Grids, considering the increasing fusion of ICT in power systems and the associated emerging threats. The research harnesses a co-simulation environment, encapsulating IT, OT, and ET layers, to model multi-stage cyberattacks and evaluate machine learning-based IDS strategies. The key observation is that process-aware IDS demonstrate superior detection capabilities, especially in scenarios closely tied to operational processes, as opposed to IT-only IDS. This improvement is notable in distinguishing complex cyber threats from regular IT activities. The findings underscore the significance of further developing sophisticated IDS benchmarks and digital twin datasets in Smart Grid environments, paving the way for more resilient cybersecurity infrastructures.