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Paradigms and Challenges for Deterrence in Cyberspace

Uribe, Eva U.; Apolis, Jeffrey J.; Bonin, Benjamin J.; Hinton, John P.; Kosydar, Andrew; Mairs, Christopher T.; Sa, Timothy; Tucker, Mark D.

In 2018 Sandia National Laboratories launched the Civilian Cyber Strategic Initiative, an ongoing multi-year effort to characterize future threats to civilian cyber infrastructures, to inform research and development efforts to detect, attribute, counter, and recover from cyber attacks, and to inform program and capability investment decisions across the Energy and Homeland Security portfolio at Sandia. One of the primary objectives of the Civilian Cyber Strategic initiative is to leverage Sandia's systems analysis capabilities to characterize future threats and to support a new theory of deterrence. Towards the goal of supporting a new theory of deterrence in cyberspace, the purpose of this study was to understand how new and existing deterrence paradigms can be applied to cyberspace, to identify unique challenges and pitfalls associated with deterring adversaries in cyberspace, and to develop preliminary ideas for how our ability to deter cyber adversaries might be improved. Our approach combined literature reviews of relevant policy documents and the academic literature with interviews of experts both at Sandia and beyond.

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Risk-based cost-benefit analysis for security assessment problems

Proceedings - International Carnahan Conference on Security Technology

Wyss, Gregory D.; Clem, John F.; Darby, John L.; Guzman, Katherine D.; Hinton, John P.; Mitchiner, K.W.

Decision-makers want to perform risk-based cost-benefit prioritization of security investments. However, strong nonlinearities in the most common physical security performance metric make it difficult to use for cost-benefit analysis. This paper extends the definition of risk for security applications and embodies this definition in a new but related security risk metric based on the degree of difficulty an adversary will encounter to successfully execute the most advantageous attack scenario. This metric is compatible with traditional cost-benefit optimization algorithms, and can lead to an objective risk-based cost-benefit method for security investment option prioritization. It also enables decision-makers to more effectively communicate the justification for their investment decisions with stakeholders and funding authorities. ©2010 IEEE.

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11 Results
11 Results