On Distinguishability of Anomalies as Physical Faults or Actuation Cyberattacks

Increased automation has created an impetus to integrate infrastructure with wide-spread connectivity in order to improve e ciency, sustainability, autonomy, and security. Nonetheless, this reliance on connectivity and the inevitability of complexity in this system increase the vulnerabilities to physical faults or degradation and external cyber-threats. However, strategies to counteract faults and cyberattacks would be widely di erent and thus it is vital to not only detect but also to identify the nature of the anomaly that is present in these systems. In this work, we propose a mathematical framework to distinguish between physical faults and cyberattack using a sliding mode based unknown input observer. Finally, we present simulation case studies to distinguish between physical faults and cyberattacks using the proposed distinguishability metric and criterion. The simulation results show that the proposed framework successfully distinguishes between faults and cyberattacks.