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20172026
most citedProving Expected Sensitivity of Probabilistic Programs

36 citations · 50 across the 7 of their papers we have counts for

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Showing 2019Show all

9 papers · 1 filter

cs.CR2019

Deciding Differential Privacy for Programs with Finite Inputs and Outputs

Gilles Barthe, Rohit Chadha, Vishal Jagannath +2

Differential privacy is a de facto standard for statistical computations over databases that contain private data. The strength of differential privacy lies in a rigorous mathemati…

cs.CR2019

Constant-Time Foundations for the New Spectre Era

Sunjay Cauligi, Craig Disselkoen, Klaus v. Gleissenthall +4

The constant-time discipline is a software-based countermeasure used for protecting high assurance cryptographic implementations against timing side-channel attacks. Constant-time…

cs.PL2019

A Probabilistic Separation Logic

Gilles Barthe, Justin Hsu, Kevin Liao

Probabilistic independence is a useful concept for describing the result of random sampling---a basic operation in all probabilistic languages---and for reasoning about groups of r…

cs.LO2019

Verifying Relational Properties using Trace Logic

Gilles Barthe, Renate Eilers, Pamina Georgiou +3

We present a logical framework for the verification of relational properties in imperative programs. Our work is motivated by relational properties which come from security applica…

cs.LG2019

Privacy Amplification by Mixing and Diffusion Mechanisms

Borja Balle, Gilles Barthe, Marco Gaboardi +1

A fundamental result in differential privacy states that the privacy guarantees of a mechanism are preserved by any post-processing of its output. In this paper we investigate unde…

cs.LG2019

Model-Agnostic Counterfactual Explanations for Consequential Decisions

Amir-Hossein Karimi, Gilles Barthe, Borja Balle +1

Predictive models are being increasingly used to support consequential decision making at the individual level in contexts such as pretrial bail and loan approval. As a result, the…