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Exploring Explicit Uncertainty for Binary Analysis (EUBA)

Leger, Michelle A.; Darling, Michael C.; Jones, Stephen T.; Matzen, Laura E.; Stracuzzi, David J.; Wilson, Andrew T.; Bueno, Denis; Christentsen, Matthew; Ginaldi, Melissa; Foulk, James W.; Heidbrink, Scott; Howell, Breannan C.; Leger, Chris; Reedy, Geoffrey; Rogers, Alisa; Williams, Jack

Reverse engineering (RE) analysts struggle to address critical questions about the safety of binary code accurately and promptly, and their supporting program analysis tools are simply wrong sometimes. The analysis tools have to approximate in order to provide any information at all, but this means that they introduce uncertainty into their results. And those uncertainties chain from analysis to analysis. We hypothesize that exposing sources, impacts, and control of uncertainty to human binary analysts will allow the analysts to approach their hardest problems with high-powered analytic techniques that they know when to trust. Combining expertise in binary analysis algorithms, human cognition, uncertainty quantification, verification and validation, and visualization, we pursue research that should benefit binary software analysis efforts across the board. We find a strong analogy between RE and exploratory data analysis (EDA); we begin to characterize sources and types of uncertainty found in practice in RE (both in the process and in supporting analyses); we explore a domain-specific focus on uncertainty in pointer analysis, showing that more precise models do help analysts answer small information flow questions faster and more accurately; and we test a general population with domain-general sudoku problems, showing that adding "knobs" to an analysis does not significantly slow down performance. This document describes our explorations in uncertainty in binary analysis.

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CSRI Summer Proceedings 2021

Smith, J.D.; Galvan, Edgar

The Computer Science Research Institute (CSRI) brings university faculty and students to Sandia National Laboratories for focused collaborative research on Department of Energy (DOE) computer and computational science problems. The institute provides an opportunity for university researches to learn about problems in computer and computational science at DOE laboratories, and help transfer results of their research to programs at the labs. Some specific CSRI research interest areas are: scalable solvers, optimization, algebraic preconditioners, graph-based, discrete, and combinatorial algorithms, uncertainty estimation, validation and verification methods, mesh generation, dynamic load-balancing, virus and other malicious-code defense, visualization, scalable cluster computers, beyond Moore’s Law computing, exascale computing tools and application design, reduced order and multiscale modeling, parallel input/output, and theoretical computer science. The CSRI Summer Program is organized by CSRI and includes a weekly seminar series and the publication of a summer proceedings.

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Credible, Automated Meshing of Images (CAMI)

Roberts, Scott A.; Donohoe, Brendan D.; Martinez, Carianne; Krygier, Michael; Hernandez-Sanchez, Bernadette A.; Foster, Collin W.; Collins, Lincoln N.; Greene, Benjamin; Noble, David R.; Norris, Chance; Potter, Kevin M.; Roberts, Christine; Neal, Kyle D.; Bernard, Sylvain R.; Schroeder, Benjamin B.; Trembacki, Bradley; Labonte, Tyler; Sharma, Krish; Ganter, Tyler; Jones, Jessica E.; Smith, Matthew D.

Abstract not provided.

Inelastic peridynamic model for molecular crystal particles

Computational Particle Mechanics

Silling, Stewart; Barr, Christopher M.; Cooper, Marcia; Lechman, Jeremy B.; Bufford, Daniel C.

The peridynamic theory of solid mechanics is applied to modeling the deformation and fracture of micrometer-sized particles made of organic crystalline material. A new peridynamic material model is proposed to reproduce the elastic–plastic response, creep, and fracture that are observed in experiments. The model is implemented in a three-dimensional, meshless Lagrangian simulation code. In the small deformation, elastic regime, the model agrees well with classical Hertzian contact analysis for a sphere compressed between rigid plates. Under higher load, material and geometrical nonlinearity is predicted, leading to fracture. The material parameters for the energetic material CL-20 are evaluated from nanoindentation test data on the cyclic compression and failure of micrometer-sized grains.

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Al-alkyls as acceptor dopant precursors for atomic-scale devices

Journal of Physics Condensed Matter

Owen, J.H.G.; Campbell, Quinn; Santini, R.; Ivie, Jeffrey A.; Baczewski, Andrew D.; Schmucker, Scott W.; Bussmann, Ezra; Misra, Shashank; Randall, J.N.

Atomically precise ultradoping of silicon is possible with atomic resists, area-selective surface chemistry, and a limited set of hydride and halide precursor molecules, in a process known as atomic precision advanced manufacturing (APAM). It is desirable to expand this set of precursors to include dopants with organic functional groups and here we consider aluminium alkyls, to expand the applicability of APAM. We explore the impurity content and selectivity that results from using trimethyl aluminium and triethyl aluminium precursors on Si(001) to ultradope with aluminium through a hydrogen mask. Comparison of the methylated and ethylated precursors helps us understand the impact of hydrocarbon ligand selection on incorporation surface chemistry. Combining scanning tunneling microscopy and density functional theory calculations, we assess the limitations of both classes of precursor and extract general principles relevant to each.

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CSRI Summer Proceedings 2021

Smith, J.D.; Galvan, Edgar

The Computer Science Research Institute (CSRI) brings university faculty and students to Sandia National Laboratories for focused collaborative research on Department of Energy (DOE) computer and computational science problems. The institute provides an opportunity for university researches to learn about problems in computer and computational science at DOE laboratories, and help transfer results of their research to programs at the labs. Some specific CSRI research interest areas are: scalable solvers, optimization, algebraic preconditioners, graph-based, discrete, and combinatorial algorithms, uncertainty estimation, validation and verification methods, mesh generation, dynamic load-balancing, virus and other malicious-code defense, visualization, scalable cluster computers, beyond Moore’s Law computing, exascale computing tools and application design, reduced order and multiscale modeling, parallel input/output, and theoretical computer science. The CSRI Summer Program is organized by CSRI and includes a weekly seminar series and the publication of a summer proceedings.

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Results 176–200 of 9,998
Results 176–200 of 9,998