Naval Cyber-Physical Anomaly Propagation Analysis Based on a Quality Assessed Graph

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Presented at CyberScience2020 2020 by

Nicolas Pelissero

Pedro Puentes

As any other infrastructure relying on cyber-physical systems (CPS), naval CPS are highly interconnectedand collect considerable data streams, on which depend multiple command and navigation decisions. Being a datadriven decision system requiring optimized supervisory control on a permanent basis, it is critical to examine the CPSvulnerability to anomalies and their propagation. This paper presents an approach to detect CPS anomalies andestimate their propagation applying a quality assessed graph, which represents the CPS physical and digitalsubsystems, combined with system variables dependencies and a set of data and information quality measuresvectors. Following the identification of variables dependencies and high-risk nodes in the CPS, data and informationquality measures reveal how system variables are modified when an anomaly is detected, also indicating itspropagation path. Taking as reference the normal state of a naval propulsion management system, four anomaliesin the form of cyber-attacks – port scan, programmable logical controller stop, and man in the middle to change themotor speed and operation of a tank valve – were produced. Three anomalies were properly detected, and their propagation path identified. These results suggest the feasibility of anomaly detection and estimation of propagationestimation in CPS, applying data and information quality analysis to a system graph.