Cyber-Physical Security Vulnerabilities Identification and Classification in Smart Manufacturing -- A Defense-in-Depth Driven Framework and Taxonomy

• URL: http://arxiv.org/abs/2501.09023v1
• Date: Sun, 29 Dec 2024 11:41:06 GMT
• Title: Cyber-Physical Security Vulnerabilities Identification and Classification in Smart Manufacturing -- A Defense-in-Depth Driven Framework and Taxonomy
• Authors: Md Habibor Rahman, Mohammed Shafae,
• Abstract summary: Existing solutions fall short in addressing the complex, domain-specific vulnerabilities of manufacturing environments.<n>This paper redefines vulnerabilities in the manufacturing context by introducing a novel characterization based on the duality between vulnerabilities and defenses.<n>We identify and classify vulnerabilities across the manufacturing cyberspace, human element, post-production inspection systems, production process monitoring, and organizational policies and procedures.
• Score: 0.0
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: The increasing cybersecurity threats to critical manufacturing infrastructure necessitate proactive strategies for vulnerability identification, classification, and assessment. Traditional approaches, which define vulnerabilities as weaknesses in computational logic or information systems, often overlook the physical and cyber-physical dimensions critical to manufacturing systems, comprising intertwined cyber, physical, and human elements. As a result, existing solutions fall short in addressing the complex, domain-specific vulnerabilities of manufacturing environments. To bridge this gap, this work redefines vulnerabilities in the manufacturing context by introducing a novel characterization based on the duality between vulnerabilities and defenses. Vulnerabilities are conceptualized as exploitable gaps within various defense layers, enabling a structured investigation of manufacturing systems. This paper presents a manufacturing-specific cyber-physical defense-in-depth model, highlighting how security-aware personnel, post-production inspection systems, and process monitoring approaches can complement traditional cyber defenses to enhance system resilience. Leveraging this model, we systematically identify and classify vulnerabilities across the manufacturing cyberspace, human element, post-production inspection systems, production process monitoring, and organizational policies and procedures. This comprehensive classification introduces the first taxonomy of cyber-physical vulnerabilities in smart manufacturing systems, providing practitioners with a structured framework for addressing vulnerabilities at both the system and process levels. Finally, the effectiveness of the proposed model and framework is demonstrated through an illustrative smart manufacturing system and its corresponding threat model.

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