An approach to cyber-physical vulnerability assessment for intelligent manufacturing systems

The rampant increase in frequency and complexity of cyber-attacks against manufacturing firms has motivated the development of identification and assessment techniques for cyber-physical vulnerabilities in manufacturing. While the field of cybersecurity assessment approaches is expansive, there is a gap in assessments for cyber-physical vulnerabilities in intelligent manufacturing systems. In response, this paper provides an approach for systematically identifying cyber-physical vulnerabilities and analyzing their potential impact in intelligent manufacturing systems. The proposed approach employs intersection mapping to identify cyber-physical vulnerabilities in manufacturing. A cyber-physical vulnerability impact analysis using decision trees then provides the manufacturer with a stoplight scale between low, medium, and high levels of cyber-physical vulnerabilities for each production process. The stoplight scale allows manufacturers to interpret assessment results in an intuitive way. Finally, a case study of the proposed approach at an applied manufacturing research facility and general recommendations to securing similar facilities from cyber-physical attacks are provided.