Assessing Model-free Anomaly Detection in Industrial Control Systems Against Generic Concealment Attacks
Alessandro Erba, Nils Ole Tippenhauer
Abstract
In recent years, a number of model-free process-based anomaly detection schemes for Industrial Control Systems (ICS) were proposed. Model-free anomaly detectors are trained directly from process data and do not require process knowledge. They are validated based on a set of public data with limited attacks present. As result, the resilience of those schemes against general concealment attacks is unclear. In addition, no structured discussion on the properties verified by the detectors exists.
Topics & Concepts
Anomaly detectionComputer scienceProcess (computing)Anomaly (physics)Resilience (materials science)Set (abstract data type)DetectorIndustrial control systemData miningData modelingProcess controlControl (management)Computer securityArtificial intelligenceSoftware engineeringTelecommunicationsProgramming languageThermodynamicsPhysicsOperating systemCondensed matter physicsSmart Grid Security and ResilienceFault Detection and Control SystemsElectrostatic Discharge in Electronics