| Title | Cyber-Physical Anomaly Detection for ICS |
| Publication Type | Conference Paper |
| Year of Publication | 2021 |
| Authors | Wüstrich, Lars, Schröder, Lukas, Pahl, Marc-Oliver |
| Conference Name | 2021 IFIP/IEEE International Symposium on Integrated Network Management (IM) |
| Date Published | may |
| Keywords | anomaly detection, Cyber-physical systems, feature extraction, finger-printing, Fingerprint recognition, ICs, ICS Anomaly Detection, integrated circuits, Physical layer, Production facilities, pubcrawl, resilience, Resiliency, Scalability, security, Sound, telecommunication traffic, Three-dimensional displays |
| Abstract | Industrial Control Systems (ICS) are complex systems made up of many components with different tasks. For a safe and secure operation, each device needs to carry out its tasks correctly. To monitor a system and ensure the correct behavior of systems, anomaly detection is used.Models of expected behavior often rely only on cyber or physical features for anomaly detection. We propose an anomaly detection system that combines both types of features to create a dynamic fingerprint of an ICS. We present how a cyber-physical anomaly detection using sound on the physical layer can be designed, and which challenges need to be overcome for a successful implementation. We perform an initial evaluation for identifying actions of a 3D printer. |
| Citation Key | wustrich_cyber-physical_2021 |
Cyber-Physical Anomaly Detection for ICS