Driving missing data at next-to-leading order

in Physical Review D (2011), 84(11), 114002

The prediction of backgrounds to new-physics signals in topologies with large missing transverse energy and jets is important to new-physics searches at the LHC. Following a CMS study, we investigate ... [more ▼]

The prediction of backgrounds to new-physics signals in topologies with large missing transverse energy and jets is important to new-physics searches at the LHC. Following a CMS study, we investigate theoretical issues in using measurements of γ+2-jet production to predict the irreducible background to searches for missing energy plus two jets that originates from Z+2-jet production where the Z boson decays to neutrinos. We compute ratios of γ+2-jet to Z+2-jet production cross sections and kinematic distributions at next-to-leading order in αs, as well as using a parton shower matched to leading-order matrix elements. The former ratios rely on the first next-to-leading-order calculation of γ+2-jet production at a hadron collider. We find that the ratios obtained in the two approximations are quite similar, making γ+2-jet production a theoretically reliable estimator for the missing energy plus two jets background. We employ a Frixione-style photon isolation, but we also show that for isolated prompt-photon production at high transverse momentum the difference between this criterion and the standard-cone isolation used by CMS is small. [less ▲]

DroidRA: Taming Reflection to Support Whole-Program Analysis of Android Apps

in The 2016 International Symposium on Software Testing and Analysis (2016, July)

Android developers heavily use reflection in their apps for legitimate reasons, but also significantly for hiding malicious actions. Unfortunately, current state-of-the-art static analysis tools for ... [more ▼]

Android developers heavily use reflection in their apps for legitimate reasons, but also significantly for hiding malicious actions. Unfortunately, current state-of-the-art static analysis tools for Android are challenged by the presence of reflective calls which they usually ignore. Thus, the results of their security analysis, e.g., for private data leaks, are inconsistent given the measures taken by malware writers to elude static detection. We propose the DroidRA instrumentation-based approach to address this issue in a non-invasive way. With DroidRA, we reduce the resolution of reflective calls to a composite constant propagation problem. We leverage the COAL solver to infer the values of reflection targets and app, and we eventually instrument this app to include the corresponding traditional Java call for each reflective call. Our approach allows to boost an app so that it can be immediately analyzable, including by such static analyzers that were not reflection-aware. We evaluate DroidRA on benchmark apps as well as on real-world apps, and demonstrate that it can allow state-of-the-art tools to provide more sound and complete analysis results. [less ▲]

Le droit à la sauce piquante n°1 - La Lettre d’Information juridique de l’économie sociale et solidaire

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Le droit à la sauce piquante N°11 – décembre 2017

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Le droit à la sauce piquante N°16 – février 2019

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Le droit à la sauce piquante N°18 – février 2020

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Le droit à la sauce piquante N°20 – juin 2020

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Le droit à la sauce piquante n°22 - Mars 2021

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Le droit à la sauce piquante n°24 - Septembre 2021

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Le droit à la sauce piquante N°4 – avril 2016

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