Scholarly Works, Industrial and Systems Engineering

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https://hdl.handle.net/10919/24292
Research articles, presentations, and other scholarship

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Browsing Scholarly Works, Industrial and Systems Engineering by Department "Hume Center for National Security and Technology"

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    Cyberphysical Security Through Resiliency: A Systems-Centric Approach
    Fleming, Cody H.; Elks, Carl R.; Bakirtzis, Georgios; Adams, Stephen C.; Carter, Bryan; Beling, Peter A.; Horowitz, Barry M. (2021-06)
    Cyberphysical systems require resiliency techniques for defense, and multicriteria resiliency problems need an approach that evaluates systems for current threats and potential design solutions. A systems-oriented view of cyberphysical security, termed Mission Aware, is proposed based on a holistic understanding of mission goals, system dynamics, and risk.
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    An ontological metamodel for cyber-physical system safety, security, and resilience coengineering
    Bakirtzis, Georgios; Sherburne, Tim; Adams, Stephen C.; Horowitz, Barry M.; Beling, Peter A.; Fleming, Cody H. (2021-06-01)
    Cyber-physical systems are complex systems that require the integration of diverse software, firmware, and hardware to be practical and useful. This increased complexity is impacting the management of models necessary for designing cyber-physical systems that are able to take into account a number of "-ilities", such that they are safe and secure and ultimately resilient to disruption of service. We propose an ontological metamodel for system design that augments an already existing industry metamodel to capture the relationships between various model elements (requirements, interfaces, physical, and functional) and safety, security, and resilient considerations. Employing this metamodel leads to more cohesive and structured modeling efforts with an overall increase in scalability, usability, and unification of already existing models. In turn, this leads to a mission-oriented perspective in designing security defenses and resilience mechanisms to combat undesirable behaviors. We illustrate this metamodel in an open-source GraphQL implementation, which can interface with a number of modeling languages. We support our proposed metamodel with a detailed demonstration using an oil and gas pipeline model.