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Improving supply chain security using big data

IEEE ISI 2013 - 2013 IEEE International Conference on Intelligence and Security Informatics: Big Data, Emergent Threats, and Decision-Making in Security Informatics

Zage, David J.; Glass, Kristin G.; Colbaugh, Richard C.

Previous attempts at supply chain risk management are often non-technical and rely heavily on policies/procedures to provide security assurances. This is particularity worrisome as there are vast volumes of data that must be analyzed and data continues to grow at unprecedented rates. In order to mitigate these issues and minimize the amount of manual inspection required, we propose the development of mathematically-based automated screening methods that can be incorporated into supply chain risk management. In particular, we look at methods for identifying deception and deceptive practices that may be present in the supply chain. We examine two classes of constraints faced by deceivers, cognitive/computational limitations and strategic tradeoffs, which can be used to developed graph-based metrics to represent entity behavior. By using these metrics with novel machine learning algorithms, we can robustly detect deceptive behavior and identify potential supply chain issues. © 2013 IEEE.

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A case for Sandia investment in complex adaptive systems science and technology

Johnson, Curtis M.; Backus, George A.; Brown, Theresa J.; Colbaugh, Richard C.; Jones, Katherine A.; Tsao, Jeffrey Y.

This white paper makes a case for Sandia National Laboratories investments in complex adaptive systems science and technology (S&T) -- investments that could enable higher-value-added and more-robustly-engineered solutions to challenges of importance to Sandia's national security mission and to the nation. Complex adaptive systems are ubiquitous in Sandia's national security mission areas. We often ignore the adaptive complexity of these systems by narrowing our 'aperture of concern' to systems or subsystems with a limited range of function exposed to a limited range of environments over limited periods of time. But by widening our aperture of concern we could increase our impact considerably. To do so, the science and technology of complex adaptive systems must mature considerably. Despite an explosion of interest outside of Sandia, however, that science and technology is still in its youth. What has been missing is contact with real (rather than model) systems and real domain-area detail. With its center-of-gravity as an engineering laboratory, Sandia's has made considerable progress applying existing science and technology to real complex adaptive systems. It has focused much less, however, on advancing the science and technology itself. But its close contact with real systems and real domain-area detail represents a powerful strength with which to help complex adaptive systems science and technology mature. Sandia is thus both a prime beneficiary of, as well as potentially a prime contributor to, complex adaptive systems science and technology. Building a productive program in complex adaptive systems science and technology at Sandia will not be trivial, but a credible path can be envisioned: in the short run, continue to apply existing science and technology to real domain-area complex adaptive systems; in the medium run, jump-start the creation of new science and technology capability through Sandia's Laboratory Directed Research and Development program; and in the long run, inculcate an awareness at the Department of Energy of the importance of supporting complex adaptive systems science through its Office of Science.

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Results 1–25 of 32
Results 1–25 of 32