1.1k citations · 2.1k across the 73 of their papers we have counts for
6 papers · 1 filter
Information Leakage Games: Exploring Information as a Utility Function
Mário S. Alvim, Konstantinos Chatzikokolakis, Yusuke Kawamoto +1
A common goal in the areas of secure information flow and privacy is to build effective defenses against unwanted leakage of information. To this end, one must be able to reason ab…
Bayes Security: A Not So Average Metric
Konstantinos Chatzikokolakis, Giovanni Cherubin, Catuscia Palamidessi +1
Security system designers favor worst-case security metrics, such as those derived from differential privacy (DP), due to the strong guarantees they provide. On the downside, these…
Survey on Causal-based Machine Learning Fairness Notions
Karima Makhlouf, Sami Zhioua, Catuscia Palamidessi
Addressing the problem of fairness is crucial to safely use machine learning algorithms to support decisions with a critical impact on people's lives such as job hiring, child malt…
Machine learning fairness notions: Bridging the gap with real-world applications
Karima Makhlouf, Sami Zhioua, Catuscia Palamidessi
Fairness emerged as an important requirement to guarantee that Machine Learning (ML) predictive systems do not discriminate against specific individuals or entire sub-populations,…
Estimating g-Leakage via Machine Learning
Marco Romanelli, Konstantinos Chatzikokolakis, Catuscia Palamidessi +1
This paper considers the problem of estimating the information leakage of a system in the black-box scenario. It is assumed that the system's internals are unknown to the learner,…
Feature selection in machine learning: Rényi min-entropy vs Shannon entropy
Catuscia Palamidessi, Marco Romanelli
Feature selection, in the context of machine learning, is the process of separating the highly predictive feature from those that might be irrelevant or redundant. Information theo…