Catuscia Palamidessi

ORCID

Publication Activity (10 Years)

Years Active: 1983-2024
Publications (10 Years): 121

Top Venues

Publications

Sayan Biswas, Catuscia Palamidessi
PRIVIC: A privacy-preserving method for incremental collection of location data. Proc. Priv. Enhancing Technol. 2024 (1) (2024)
Héber Hwang Arcolezi, Karima Makhlouf, Catuscia Palamidessi
(Local) Differential Privacy has NO Disparate Impact on Fairness. CoRR (2023)
Filippo Galli, Catuscia Palamidessi, Tommaso Cucinotta
Online Sensitivity Optimization in Differentially Private Learning. CoRR (2023)
Mireya Jurado, Ramon G. Gonze, Mário S. Alvim, Catuscia Palamidessi
Analyzing the Shuffle Model Through the Lens of Quantitative Information Flow. CSF (2023)
Héber Hwang Arcolezi, Selene Cerna, Catuscia Palamidessi
On the Utility Gain of Iterative Bayesian Update for Locally Differentially Private Mechanisms. CoRR (2023)
Filippo Galli, Sayan Biswas, Kangsoo Jung, Tommaso Cucinotta, Catuscia Palamidessi
Group Privacy for Personalized Federated Learning. ICISSP (2023)
Filippo Galli, Kangsoo Jung, Sayan Biswas, Catuscia Palamidessi, Tommaso Cucinotta
Advancing Personalized Federated Learning: Group Privacy, Fairness, and Beyond. SN Comput. Sci. 4 (6) (2023)
Sebastian Simon, Cezara Petrui, Carlos Pinzón, Catuscia Palamidessi
Obfuscation Padding Schemes that Minimize Rényi Min-Entropy for Privacy. ISPEC (2023)
Karima Makhlouf, Héber Hwang Arcolezi, Sami Zhioua, Ghassen Ben Brahim, Catuscia Palamidessi
On the Impact of Multi-dimensional Local Differential Privacy on Fairness. CoRR (2023)
Héber Hwang Arcolezi, Karima Makhlouf, Catuscia Palamidessi
(Local) Differential Privacy has NO Disparate Impact on Fairness. DBSec (2023)
Selene Cerna, Catuscia Palamidessi
On the application and impact of ε-DP and fairness in ambulance engagement time prediction. Tiny Papers @ ICLR (2023)
Catuscia Palamidessi
Chair's Letter. ACM SIGLOG News 10 (1) (2023)
Ganesh Del Grosso, Georg Pichler, Catuscia Palamidessi, Pablo Piantanida
Bounding information leakage in machine learning. Neurocomputing 534 (2023)
Héber Hwang Arcolezi, Selene Cerna, Catuscia Palamidessi
On the Utility Gain of Iterative Bayesian Update for Locally Differentially Private Mechanisms. DBSec (2023)
Filippo Galli, Kangsoo Jung, Sayan Biswas, Catuscia Palamidessi, Tommaso Cucinotta
Advancing Personalized Federated Learning: Group Privacy, Fairness, and Beyond. CoRR (2023)
Ruta Binkyte, Carlos Pinzón, Szilvia Lestyán, Kangsoo Jung, Héber Hwang Arcolezi, Catuscia Palamidessi
Causal Discovery Under Local Privacy. CoRR (2023)
Héber Hwang Arcolezi, Sébastien Gambs, Jean-François Couchot, Catuscia Palamidessi
On the Risks of Collecting Multidimensional Data Under Local Differential Privacy. Proc. VLDB Endow. 16 (5) (2023)
Héber Hwang Arcolezi, Carlos Pinzón, Catuscia Palamidessi, Sébastien Gambs
Frequency Estimation of Evolving Data Under Local Differential Privacy. EDBT (2023)
Ruta Binkyte, Daniele Gorla, Catuscia Palamidessi
BaBE: Enhancing Fairness via Estimation of Latent Explaining Variables. CoRR (2023)
Daniele Gorla, Louis Jalouzot, Federica Granese, Catuscia Palamidessi, Pablo Piantanida
On the (Im)Possibility of Estimating Various Notions of Differential Privacy (short paper). ICTCS (2023)
Catuscia Palamidessi
Local Methods for Privacy Protection and Impact on Fairness. CODASPY (2023)
Natasha Fernandes, Annabelle McIver, Catuscia Palamidessi, Ming Ding
Universal optimality and robust utility bounds for metric differential privacy. J. Comput. Secur. 31 (5) (2023)
Mireya Jurado, Ramon G. Gonze, Mário S. Alvim, Catuscia Palamidessi
Analyzing the Shuffle Model through the Lens of Quantitative Information Flow. CoRR (2023)
Konstantinos Chatzikokolakis, Giovanni Cherubin, Catuscia Palamidessi, Carmela Troncoso
Bayes Security: A Not So Average Metric. CSF (2023)
Daniele Gorla, Louis Jalouzot, Federica Granese, Catuscia Palamidessi, Pablo Piantanida
On the (Im)Possibility of Estimating Various Notions of Differential Privacy. CoRR (2022)
Ruta Binkyte, Karima Makhlouf, Carlos Pinzón, Sami Zhioua, Catuscia Palamidessi
Causal Discovery for Fairness. AFCP (2022)
Ugur-Ilker Atmaca, Sayan Biswas, Carsten Maple, Catuscia Palamidessi
A privacy preserving querying mechanism with high utility for electric vehicles. CoRR (2022)
Ganesh Del Grosso, Hamid Jalalzai, Georg Pichler, Catuscia Palamidessi, Pablo Piantanida
Leveraging Adversarial Examples to Quantify Membership Information Leakage. CoRR (2022)
Héber Hwang Arcolezi, Sébastien Gambs, Jean-François Couchot, Catuscia Palamidessi
On the Risks of Collecting Multidimensional Data Under Local Differential Privacy. CoRR (2022)
Héber Hwang Arcolezi, Jean-François Couchot, Sébastien Gambs, Catuscia Palamidessi, Majid Zolfaghari
Multi-Freq-LDPy: Multiple Frequency Estimation Under Local Differential Privacy in Python. CoRR (2022)
Karima Makhlouf, Sami Zhioua, Catuscia Palamidessi
Identifiability of Causal-based Fairness Notions: A State of the Art. CoRR (2022)
Filippo Galli, Sayan Biswas, Kangsoo Jung, Catuscia Palamidessi, Tommaso Cucinotta
Group privacy for personalized federated learning. CoRR (2022)
Ehab ElSalamouny, Catuscia Palamidessi
Reconstruction of the distribution of sensitive data under free-will privacy. CoRR (2022)
Sayan Biswas, Kangsoo Jung, Catuscia Palamidessi
Tight Differential Privacy Guarantees for the Shuffle Model with k-Randomized Response. CoRR (2022)
Natasha Fernandes, Annabelle McIver, Catuscia Palamidessi, Ming Ding
Universal Optimality and Robust Utility Bounds for Metric Differential Privacy. CoRR (2022)
Guilherme Alves, Fabien Bernier, Miguel Couceiro, Karima Makhlouf, Catuscia Palamidessi, Sami Zhioua
Survey on Fairness Notions and Related Tensions. CoRR (2022)
Ruta Binkyte-Sadauskiene, Karima Makhlouf, Carlos Pinzón, Sami Zhioua, Catuscia Palamidessi
Causal Discovery for Fairness. CoRR (2022)
Héber Hwang Arcolezi, Carlos Pinzón, Catuscia Palamidessi, Sébastien Gambs
Frequency Estimation of Evolving Data Under Local Differential Privacy. CoRR (2022)
Héber Hwang Arcolezi, Jean-François Couchot, Sébastien Gambs, Catuscia Palamidessi, Majid Zolfaghari
Multi-Freq-LDPy: Multiple Frequency Estimation Under Local Differential Privacy in Python. ESORICS (3) (2022)
Ganesh Del Grosso, Hamid Jalalzai, Georg Pichler, Catuscia Palamidessi, Pablo Piantanida
Leveraging Adversarial Examples to Quantify Membership Information Leakage. CVPR (2022)
Sebastian Simon, Cezara Petrui, Carlos Pinzón, Catuscia Palamidessi
Minimizing Information Leakage under Padding Constraints. CoRR (2022)
Mário S. Alvim, Konstantinos Chatzikokolakis, Yusuke Kawamoto, Catuscia Palamidessi
Information Leakage Games: Exploring Information as a Utility Function. ACM Trans. Priv. Secur. 25 (3) (2022)
Carlos Pinzón, Catuscia Palamidessi, Pablo Piantanida, Frank Valencia
On the Impossibility of Non-trivial Accuracy in Presence of Fairness Constraints. AAAI (2022)
Natasha Fernandes, Annabelle McIver, Catuscia Palamidessi, Ming Ding
Universal Optimality and Robust Utility Bounds for Metric Differential Privacy. CSF (2022)
Sayan Biswas, Kangsoo Jung, Catuscia Palamidessi
Tight Differential Privacy Blanket for Shuffle Model. CoRR (2022)
Sayan Biswas, Catuscia Palamidessi
Three-way optimization of privacy and utility of location data. CoRR (2022)
Sayan Biswas, Kangsoo Jung, Catuscia Palamidessi
An Incentive Mechanism for Trading Personal Data in Data Markets. CoRR (2021)
Ganesh Del Grosso, Georg Pichler, Catuscia Palamidessi, Pablo Piantanida
Bounding Information Leakage in Machine Learning. CoRR (2021)
Kangsoo Jung, Sayan Biswas, Catuscia Palamidessi
Establishing the Price of Privacy in Federated Data Trading. Protocols, Strands, and Logic (2021)
Kangsoo Jung, Sayan Biswas, Catuscia Palamidessi
Establishing the Price of Privacy in Federated Data Trading. CoRR (2021)
Karima Makhlouf, Sami Zhioua, Catuscia Palamidessi
On the Applicability of Machine Learning Fairness Notions. SIGKDD Explor. 23 (1) (2021)
Federica Granese, Daniele Gorla, Catuscia Palamidessi
Enhanced models for privacy and utility in continuous-time diffusion networks. Int. J. Inf. Sec. 20 (5) (2021)
Federica Granese, Marco Romanelli, Daniele Gorla, Catuscia Palamidessi, Pablo Piantanida
DOCTOR: A Simple Method for Detecting Misclassification Errors. NeurIPS (2021)
Carlos Pinzón, Catuscia Palamidessi, Pablo Piantanida, Frank Valencia
On the impossibility of non-trivial accuracy under fairness constraints. CoRR (2021)
Karima Makhlouf, Sami Zhioua, Catuscia Palamidessi
Machine learning fairness notions: Bridging the gap with real-world applications. Inf. Process. Manag. 58 (5) (2021)
Sayan Biswas, Kangsoo Jung, Catuscia Palamidessi
An Incentive Mechanism for Trading Personal Data in Data Markets. ICTAC (2021)
Mireya Jurado, Catuscia Palamidessi, Geoffrey Smith
A Formal Information-Theoretic Leakage Analysis of Order-Revealing Encryption. CSF (2021)
Nathalie Bertrand, Luca de Alfaro, Rob van Glabbeek, Catuscia Palamidessi, Nobuko Yoshida
CONCUR Test-Of-Time Award 2021 (Invited Paper). CONCUR (2021)
Abhishek Kumar Mishra, Aline Carneiro Viana, Nadjib Achir, Catuscia Palamidessi
Public Wireless Packets Anonymously Hurt You. LCN (2021)
Federica Granese, Marco Romanelli, Daniele Gorla, Catuscia Palamidessi, Pablo Piantanida
DOCTOR: A Simple Method for Detecting Misclassification Errors. CoRR (2021)
Marco Romanelli, Konstantinos Chatzikokolakis, Catuscia Palamidessi, Pablo Piantanida
Estimating g-Leakage via Machine Learning. CCS (2020)
Catuscia Palamidessi, Marco Romanelli
Modern Applications of Game-Theoretic Principles (Invited Paper). CONCUR (2020)
Karima Makhlouf, Sami Zhioua, Catuscia Palamidessi
Survey on Causal-based Machine Learning Fairness Notions. CoRR (2020)
Moreno Falaschi, Catuscia Palamidessi, Marco Romanelli
Derivation of Constraints from Machine Learning Models and Applications to Security and Privacy. Gabbrielli's Festschrift (2020)
Marco Romanelli, Konstantinos Chatzikokolakis, Catuscia Palamidessi, Pablo Piantanida
Estimating g-Leakage via Machine Learning. CoRR (2020)
Valentina Castiglioni, Konstantinos Chatzikokolakis, Catuscia Palamidessi
A logical characterization of differential privacy. Sci. Comput. Program. 188 (2020)
Mário S. Alvim, Konstantinos Chatzikokolakis, Yusuke Kawamoto, Catuscia Palamidessi
Information Leakage Games: Exploring Information as a Utility Function. CoRR (2020)
Moreno Falaschi, Maurizio Gabbrielli, Carlos Olarte, Catuscia Palamidessi
Dynamic Slicing for Concurrent Constraint Languages. Fundam. Informaticae 177 (3-4) (2020)
Catuscia Palamidessi, Marco Romanelli
Feature selection in machine learning: Rényi min-entropy vs Shannon entropy. CoRR (2020)
Konstantinos Chatzikokolakis, Giovanni Cherubin, Catuscia Palamidessi, Carmela Troncoso
The Bayes Security Measure. CoRR (2020)
Marco Romanelli, Konstantinos Chatzikokolakis, Catuscia Palamidessi
Optimal Obfuscation Mechanisms via Machine Learning. CSF (2020)
Karima Makhlouf, Sami Zhioua, Catuscia Palamidessi
On the Applicability of ML Fairness Notions. CoRR (2020)
Ehab ElSalamouny, Catuscia Palamidessi
Generalized Iterative Bayesian Update and Applications to Mechanisms for Privacy Protection. EuroS&P (2020)
Konstantinos Chatzikokolakis, Natasha Fernandes, Catuscia Palamidessi
Refinement Orders for Quantitative Information Flow and Differential Privacy. J. Cybersecur. Priv. 1 (1) (2020)
Konstantinos Chatzikokolakis, Natasha Fernandes, Catuscia Palamidessi
Comparing Systems: Max-Case Refinement Orders and Application to Differential Privacy. CSF (2019)
Daniele Gorla, Federica Granese, Catuscia Palamidessi
Enhanced Models for Privacy and Utility in Continuous-Time Diffusion Networks. ICTAC (2019)
Mário S. Alvim, Konstantinos Chatzikokolakis, Annabelle McIver, Carroll Morgan, Catuscia Palamidessi, Geoffrey Smith
An axiomatization of information flow measures. Theor. Comput. Sci. 777 (2019)
Natasha Fernandes, Lefki Kacem, Catuscia Palamidessi
Utility-Preserving Privacy Mechanisms for Counting Queries. CoRR (2019)
Ehab ElSalamouny, Catuscia Palamidessi
Full Convergence of the Iterative Bayesian Update and Applications to Mechanisms for Privacy Protection. CoRR (2019)
Natasha Fernandes, Lefki Kacem, Catuscia Palamidessi
Utility-Preserving Privacy Mechanisms for Counting Queries. Models, Languages, and Tools for Concurrent and Distributed Programming (2019)
Ali Kassem, Gergely Ács, Claude Castelluccia, Catuscia Palamidessi
Differential Inference Testing: A Practical Approach to Evaluate Sanitizations of Datasets. IEEE Symposium on Security and Privacy Workshops (2019)
Giovanni Cherubin, Konstantinos Chatzikokolakis, Catuscia Palamidessi
F-BLEAU: Fast Black-Box Leakage Estimation. IEEE Symposium on Security and Privacy (2019)
Giovanni Cherubin, Konstantinos Chatzikokolakis, Catuscia Palamidessi
F-BLEAU: Fast Black-box Leakage Estimation. CoRR (2019)
Adriano Di Luzio, Aline Carneiro Viana, Konstantinos Chatzikokolakis, Georgi Dikov, Catuscia Palamidessi, Julinda Stefa
Catch me if you can: how geo-indistinguishability affects utility in mobility-based geographic datasets. LocalRec@SIGSPATIAL (2019)
Marco Romanelli, Catuscia Palamidessi, Konstantinos Chatzikokolakis
Generating Optimal Privacy-Protection Mechanisms via Machine Learning. CoRR (2019)
Valentina Castiglioni, Konstantinos Chatzikokolakis, Catuscia Palamidessi
A Logical Characterization of Differential Privacy via Behavioral Metrics. FACS (2018)
Mário S. Alvim, Konstantinos Chatzikokolakis, Yusuke Kawamoto, Catuscia Palamidessi
A Game-Theoretic Approach to Information-Flow Control via Protocol Composition. CoRR (2018)
Mário S. Alvim, Konstantinos Chatzikokolakis, Catuscia Palamidessi, Anna Pazii
Metric-based local differential privacy for statistical applications. CoRR (2018)
Mário S. Alvim, Konstantinos Chatzikokolakis, Yusuke Kawamoto, Catuscia Palamidessi
Leakage and Protocol Composition in a Game-Theoretic Perspective. POST (2018)
Mário S. Alvim, Konstantinos Chatzikokolakis, Yusuke Kawamoto, Catuscia Palamidessi
A Game-Theoretic Approach to Information-Flow Control via Protocol Composition. Entropy 20 (5) (2018)
Mário S. Alvim, Konstantinos Chatzikokolakis, Yusuke Kawamoto, Catuscia Palamidessi
Leakage and Protocol Composition in a Game-Theoretic Perspective. CoRR (2018)
Catuscia Palamidessi, Marco Romanelli
Feature Selection with Rényi Min-Entropy. ANNPR (2018)
Mário S. Alvim, Konstantinos Chatzikokolakis, Catuscia Palamidessi, Anna Pazii
Invited Paper: Local Differential Privacy on Metric Spaces: Optimizing the Trade-Off with Utility. CSF (2018)
Thomas Eiter, Javier Esparza, Catuscia Palamidessi, Gordon D. Plotkin, Natarajan Shankar
Alonzo Church Award 2018 - Call for Nominations. Bull. EATCS 124 (2018)
Lefki Kacem, Catuscia Palamidessi
Geometric Noise for Locally Private Counting Queries. PLAS@CCS (2018)
Natarajan Shankar, Catuscia Palamidessi, Gordon D. Plotkin, Moshe Y. Vardi
Alonzo Church Award 2017 - Call for Nominations. Bull. EATCS 121 (2017)
Yusuke Kawamoto, Konstantinos Chatzikokolakis, Catuscia Palamidessi
On the Compositionality of Quantitative Information Flow. Log. Methods Comput. Sci. 13 (3) (2017)
Konstantinos Chatzikokolakis, Serge Haddad, Ali Kassem, Catuscia Palamidessi
Trading Optimality for Performance in Location Privacy. CoRR (2017)
Konstantinos Chatzikokolakis, Ehab ElSalamouny, Catuscia Palamidessi
Efficient Utility Improvement for Location Privacy. Proc. Priv. Enhancing Technol. 2017 (4) (2017)
Konstantinos Chatzikokolakis, Ehab ElSalamouny, Catuscia Palamidessi, Anna Pazii
Methods for Location Privacy: A comparative overview. Found. Trends Priv. Secur. 1 (4) (2017)

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Publication Activity (10 Years)

Top Topics

Top Venues

Catuscia Palamidessi