HyperPardinus extends Alloy to support specification and model checking of hyperproperties over relational design models by interfacing with low-level hyperproperty checkers.
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3 Pith papers cite this work. Polarity classification is still indexing.
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The authors provide a systematization of differentially private graph release methods along with an objective-based framework and two illustrative evaluations for social network analysts.
Supervised ML on EM side-channel data and cpufreq DVFS states identifies known applications and flags unknown ones with at least 85% accuracy on Snapdragon 820 ARMv8 hardware.
citing papers explorer
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Model checking of hyperproperties for high-level relational models
HyperPardinus extends Alloy to support specification and model checking of hyperproperties over relational design models by interfacing with low-level hyperproperty checkers.
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SoK: Practical Aspects of Releasing Differentially Private Graphs
The authors provide a systematization of differentially private graph release methods along with an objective-based framework and two illustrative evaluations for social network analysts.
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Application Inference using Machine Learning based Side Channel Analysis
Supervised ML on EM side-channel data and cpufreq DVFS states identifies known applications and flags unknown ones with at least 85% accuracy on Snapdragon 820 ARMv8 hardware.