Detection of faults and intrusions in cyber-physical systems from physical correlations

Cyber-physical systems are critical infrastructures crucial to the reliable delivery of energy and other resources, and to the stable functioning of automatic and control architectures. These systems are composed of interdependent physical, control and communications networks described by disparate mathematical models creating scientific challenges that go well beyond the modeling and analysis of the individual networks. A key challenge in cyber-physical defense is a fast online detection and localization of faults and intrusions without a prior knowledge of the failure type. We describe a set of techniques for an efficient identification of faults from correlations in physical signals, assuming that the minimal amount of information on the system is available. The performance of detection method is illustrated on data collected from a large building automation system.

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