Publications

Rigorous methods and models are needed to quantify, measure, and increase the cyber resilience of critical infrastructure. An adversary may exploit vulnerabilities in the vital networks such as industrial control systems (ICS) associated with critical infrastructure (e.g., energy, financial, transportation, security), in order to achieve harmful consequences. In cyber systems, the number of vulnerabilities may be large, the attack surface changes over time, and the problem consists of both technical and non-technical factors (e.g., errors in software and human error). Given this complex and dynamic landscape, strategically mitigating risk is important, where “risk” considers both the probability of an event and the consequences if that event occurs. One way to decrease risk is to address consequences by ensuring that critical infrastructure is resilient. In this context, resilience is characterized by the magnitude and duration of a deviation from targeted performance levels, given a disruption. Increasing resilience decreases the consequences of a successful attack.

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Manufacturing affects all three dimensions of sustainability: economy, environment, and society. This paper addresses the last of these dimensions. It explores social impacts identified by national level social indicators, frameworks, and principles. The effects of manufacturing on social performance are framed for different stakeholder groups with associated social needs. Methodology development as well as various challenges for social life cycle assessment (S-LCA) are further examined. Efforts to integrate social and another dimension of sustainability are considered, with attention to globalization challenges, including offshoring and reshoring. The paper concludes with a summary of key takeaways and promising directions for future work.

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Increasing connectivity, use of digital computation, and off-site data storage provide potential for dramatic improvements in manufacturing productivity, quality, and cost. However, there are also risks associated with the increased volume and pervasiveness of data that are generated and potentially accessible to competitors or adversaries. Enterprises have experienced cyber attacks that exfiltrate confidential and/or proprietary data, alter information to cause an unexpected or unwanted effect, and destroy capital assets. Manufacturers need tools to incorporate these risks into their existing risk management processes. This paper establishes a framework that considers the data flows within a manufacturing enterprise and throughout its supply chain. The framework provides several mechanisms for identifying generic and manufacturing-specific vulnerabilities and is illustrated with details pertinent to an automotive manufacturer. In addition to providing manufacturers with insights into their potential data risks, this framework addresses an outcome identified by the NIST Cybersecurity Framework.