Publications

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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The development of multi-dimensional statistical methods has been demonstrated on variable contact time (VCT) 29Si{1H} cross-polarization magic angle spinning (CP/MAS) data sets collected using Carr-Purcell-Meiboom-Gill (CPMG) type acquisition. These methods utilize the transformation of the collected 2D VCT data set into a 3D data set and use tensor-rank decomposition to extract the spectral components that vary as a function of transverse relaxation time (T2) and CP contact time. The result is a data dense spectral set that can be used to reconstruct CP/MAS spectra at any contact time with a high signal to noise ratio and with an excellent agreement to 29Si{1H} CP/MAS spectra collected using conventional acquisition. These CPMG data can be collected in a fraction of time that would be required to collect a conventional VCT data set. We demonstrate the method on samples of functionalized mesoporous silica materials and show that the method can provide valuable surface specific information about their functional chemistry.