Trust and Security Analyzer for Collaborative Digital Manufacturing Ecosystems

Abstract

To ensure competitiveness and to meet current market demands, the manufacturing industry continues to evolve into a more agile and integrated operating environment. Digital thread provides vital technology enablers to support this and drive the digitalization of the manufacturing sector to improve product quality, reduce time to market, support customization, etc. Digital thread capabilities provide the foundation for manufacturers to create digital twins; a virtual replica of a physical process, system, or asset supporting data-driven analysis and optimization. Connecting multiple digital twins distributed across owners, networks, and domains will create collaborative ecosystems. Since various systems need to connect to facilitate this ecosystem, trust and security are significant concerns. This paper proposes a trust and security analyzer that will aid in evaluating the trustworthiness of individual digital twins. Security, resilience, reliability, uncertainty, dependability, and goal analysis are the primary evaluation criteria for the proposed analyzer. When the trustworthiness of an individual digital twin increases, so too does the overall collaborative ecosystem.