Catuscia Palamidessi

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Information Leakage Games: Exploring Information as a Utility Function

A common goal in the areas of secure information flow and privacy is to ...
12/22/2020 ∙ by Mário S. Alvim, et al. ∙ 0 ∙ share

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The Bayes Security Measure

Security system designers favor worst-case security measures, such as th...
11/06/2020 ∙ by Konstantinos Chatzikokolakis, et al. ∙ 0 ∙ share

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Survey on Causal-based Machine Learning Fairness Notions

Addressing the problem of fairness is crucial to safely use machine lear...
10/19/2020 ∙ by Karima Makhlouf, et al. ∙ 0 ∙ share

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On the Applicability of ML Fairness Notions

ML-based predictive systems are increasingly used to support decisions w...
06/30/2020 ∙ by Karima Makhlouf, et al. ∙ 0 ∙ share

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Estimating g-Leakage via Machine Learning

This paper considers the problem of estimating the information leakage o...
05/09/2020 ∙ by Marco Romanelli, et al. ∙ 0 ∙ share

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Feature selection in machine learning: Rényi min-entropy vs Shannon entropy

Feature selection, in the context of machine learning, is the process of...
01/27/2020 ∙ by Catuscia Palamidessi, et al. ∙ 0 ∙ share

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Full Convergence of the Iterative Bayesian Update and Applications to Mechanisms for Privacy Protection

The iterative Bayesian update (IBU) and the matrix inversion (INV) are t...
09/06/2019 ∙ by Ehab ElSalamouny, et al. ∙ 0 ∙ share

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Utility-Preserving Privacy Mechanisms for Counting Queries

Differential privacy (DP) and local differential privacy (LPD) are frame...
06/28/2019 ∙ by Natasha Fernandes, et al. ∙ 0 ∙ share

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Generating Optimal Privacy-Protection Mechanisms via Machine Learning

We consider the problem of obfuscating sensitive information while prese...
04/01/2019 ∙ by Marco Romanelli, et al. ∙ 0 ∙ share

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F-BLEAU: Fast Black-box Leakage Estimation

We consider the problem of measuring how much a system reveals about its...
02/04/2019 ∙ by Giovanni Cherubin, et al. ∙ 0 ∙ share

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Metric-based local differential privacy for statistical applications

Local differential privacy (LPD) is a distributed variant of differentia...
05/03/2018 ∙ by Mário S. Alvim, et al. ∙ 0 ∙ share

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A Game-Theoretic Approach to Information-Flow Control via Protocol Composition

In the inference attacks studied in Quantitative Information Flow (QIF),...
03/27/2018 ∙ by Mário S. Alvim, et al. ∙ 0 ∙ share

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Leakage and Protocol Composition in a Game-Theoretic Perspective

In the inference attacks studied in Quantitative Information Flow (QIF),...
02/27/2018 ∙ by Mário S. Alvim, et al. ∙ 0 ∙ share

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Catuscia Palamidessi

Featured Co-authors

Carmela Troncoso

Pablo Piantanida

Yusuke Kawamoto

Mário S. Alvim

Konstantinos Chatzikokolakis

Natasha Fernandes

Marco Romanelli

Anna Pazii

Karima Makhlouf

Giovanni Cherubin

Ehab ElSalamouny

Information Leakage Games: Exploring Information as a Utility Function

The Bayes Security Measure

Survey on Causal-based Machine Learning Fairness Notions

On the Applicability of ML Fairness Notions

Estimating g-Leakage via Machine Learning

Feature selection in machine learning: Rényi min-entropy vs Shannon entropy

Full Convergence of the Iterative Bayesian Update and Applications to Mechanisms for Privacy Protection

Utility-Preserving Privacy Mechanisms for Counting Queries

Generating Optimal Privacy-Protection Mechanisms via Machine Learning

F-BLEAU: Fast Black-box Leakage Estimation

Metric-based local differential privacy for statistical applications

A Game-Theoretic Approach to Information-Flow Control via Protocol Composition

Leakage and Protocol Composition in a Game-Theoretic Perspective