Privacy in Machine Learning

Privacy in Machine Learning Publications

Georgi Ganev, Bristena Oprisanu, Emiliano De Cristofaro
Robin Hood and Matthew Effects – Differential Privacy Has Disparate Impact on Synthetic Data
arXiv:2109.11429
pre-print

Bristena Oprisanu, Georgi Ganev, Emiliano De Cristofaro
Measuring Utility and Privacy of Synthetic Genomic Data
arXiv 2102.03314
pre-print

Mohammad Naseri, Jamie Hayes, Emiliano De Cristofaro
Local and Central Differential Privacy for Robustness and Privacy in Federated Learning
29th Network and Distributed System Security Symposium (NDSS 2022)
pre-print

Yugeng Liu, Rui Wen, Xinlei He, Ahmed Salem, Zhikun Zhang, Michael Backes, Emiliano De Cristofaro, Mario Fritz, Yang Zhang
ML-Doctor: Holistic Risk Assessment of Inference Attacks Against Machine Learning Models
31st USENIX Security Symposium (Usenix Security 2022)
pre-print

Emiliano De Cristofaro
A Critical Overview of Privacy in Machine Learning
IEEE Security & Privacy Magazine, Volume 19, Issue 4, July-August 2021
pdf

Apostolos Pyrgelis, Carmela Troncoso, and Emiliano De Cristofaro
Measuring Membership Privacy on Aggregate Location Time-Series
ACM International Conference on Measurement and Modeling of Computer Systems (SIGMETRICS 2020)
pdf video

Luca Melis, Congzheng Song, Emiliano De Cristofaro, and Vitaly Shmatikov
Exploiting Unintended Feature Leakage in Collaborative Learning
40th IEEE Symposium on Security & Privacy (S&P 2019)
pdf video

Vincent Primault, Vasileios Lampos, Ingemar Cox, and Emiliano De Cristofaro
Privacy-Preserving Crowd-Sourcing of Web Searches with Private Data Donor
28th The Web Conference (WWW 2019)
pdf

Jamie Hayes, Luca Melis, George Danezis, Emiliano De Cristofaro
LOGAN: Membership Inference Attacks Against Generative Models
Proceedings on Privacy Enhancing Technologies, Vol. 2019, Issue 1 (PoPETS 2019)
pdf

Luca Melis, Apostolos Pyrgelis, Emiliano De Cristofaro
On Collaborative Predictive Blacklisting
ACM SIGCOMM’s Computer Communication Review (CCR), Vol. 48, No. 5, Oct. 2018
full version

Gergely Acs, Luca Melis, Claude Castelluccia, Emiliano De Cristofaro (Extended Version)
Differentially Private Mixture of Generative Neural Networks
IEEE Transactions on Knowledge and Data Engineering (TKDE 2018)
pdf

Apostolos Pyrgelis, Carmela Troncoso, Emiliano De Cristofaro
Knock Knock, Who’s There? Membership Inference on Aggregate Location Data
25th Network and Distributed System Security Symposium (NDSS 2018)
distinguished paper award INRIA-CNIL privacy protection award runner-up
full version blog video

Gergely Acs, Luca Melis, Claude Castelluccia, Emiliano De Cristofaro
Differentially Private Mixture of Generative Neural Networks
17th IEEE International Conference on Data Mining (ICDM 2017)
full version

Apostolos Pyrgelis, Carmela Troncoso, Emiliano De Cristofaro
What Does The Crowd Say About You? Evaluating Aggregation-based Location Privacy
Proceedings on Privacy Enhancing Technologies, Vol. 2017, Issue 4 (PoPETS 2017)
pdf

Luca Melis, George Danezis, Emiliano De Cristofaro
Efficient Private Statistics with Succinct Sketches
23rd Network and Distributed System Security Symposium (NDSS 2016)
2017 data protection by design award (from Catalan data protection authority)
pdf blog

Julien Freudiger, Emiliano De Cristofaro, Alex Brito
Controlled Data Sharing for Collaborative Predictive Blacklisting
12th Conference on Detection of Intrusions and Malware & Vulnerability Assessment (DIMVA 2015)
full version