@inproceedings{213227,

title = {Cyber-Physical Anomaly Detection for ICS},

author = {Lars Wuestrich and Lukas Schr\"{o}der and Marc-Oliver Pahl},

url = {http://xxxxx/213227.pdf},

year  = {2021},

date = {2021-05-01},

booktitle = {IFIP/IEEE International Symposium on Integrated Network Management co-located with IM},

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 systems are 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 such a system can be designed and which challenges need to be overcome for a successful implementation.},

keywords = {and Dependability, Data and device security, Other aspects relevant to manage IoT systems., resilience, Security and Privacy, Survivability, Validation and Verification of data and functional},

pubstate = {published},

tppubtype = {inproceedings}

}