Causal Reasoning for Real-Time Attack Identification in Cyber-Physical Systems
About the project
We propose to develop computationally efficient machine learning algorithms and tools for attack detection and identification based on a novel, scalable representation of the physical system state, the communication protocol state, and the IT infrastructure’s security state maintained based on noisy observations and measurements from the physical and the IT infrastructure. The key contribution is to learn a succinct representation of the security state of the IT infrastructure that allows computationally efficient belief updates in real-time and enables to jointly account for the evolution of the state of the physical system, communication protocols, and infrastructure for accurate detection of attacks and identification through causal reasoning based on learnt dependency models. The research will help address questions such as how to achieve real-time situational awareness in complex IT infrastructures, develop anomaly detectors with low false positive and false negative rates, and use information about IT infrastructure to improve attack identification. The project leverages the expertise of three research teams, from KTH, UIUC, and MIT, with extensive expertise in cyber-physical systems security, smart grids, and anomaly detection.
Modern SCADA systems rely on IP-based communication protocols that are primarily event-driven and follow a publish-subscribe model. The timing and content of protocol messages emerge from interactions between the physical system state and the protocol’s internal state – as an effect, traditional approaches to anomaly detection result in excessive false positives and, ultimately, alarm fatigue.
The project is a collaboration between KTH Royal Institute of Technology, the University of Illinois at Urbana-Champaign and MIT.
Professor, Division of Network and Systems Engineering at KTH, Strategic Research Committee, Chair working group Cooperate, PI of research project Susan’s Ride on Campus2030, PI of research project Causal reasoning for real-time attack identification in cyber-physical systems, Co-PI of research project Learning in Routing Games for Sustainable Electromobility, Digital Futures Faculty+46 8 790 42 53
Professor, Division of Decision and Control Systems at KTH EECS, Strategic Research Committee, Chair Working group Trust, PI of research project Learning in Routing Games for Sustainable Electromobility (RoSE), Co-PI of research project Causal Reasoning for Real-Time Attack Identification in Cyber-Physical Systems, Co-PI of research project Decision-making in Critical Societal Infrastructures (DEMOCRITUS), Digital Futures Faculty+46 8 790 72 94
Associate Professor, Civil and Environmental Engineering Massachusetts Institute of Technologyamins@mit.edu