Trustworthy Machine Learning
This page provides a non-exhaustive list of my publications related to security and privacy in/for machine learning. For each entry, a link to an open-access version of the paper is also provided.
Meenatchi Sundaram Muthu Selva Annamalai, Emiliano De Cristofaro
Nearly Tight Black-Box Auditing of Differentially Private Machine Learning
38th Annual Conference on Neural Information Processing Systems (NeurIPS 2024)
pre-print
Georgi Ganev, Kai Xu, Emiliano De Cristofaro
Graphical vs. Deep Generative Models: Measuring the Impact of Differentially Private Mechanisms and Budgets on Utility
31st ACM Conference on Computer and Communications Security (ACM CCS 2024)
full version
Meenatchi Sundaram Muthu Selva Annamalai, Georgi Ganev, Emiliano De Cristofaro
“What do you want from theory alone?” Experimenting with Tight Auditing of Differentially Private Synthetic Data Generation
33st USENIX Security Symposium (Usenix Security 2024)
pdf
Mohammad Naseri, Yufei Han, Emiliano De Cristofaro
BadVFL: Backdoor Attacks in Vertical Federated Learning
45th IEEE Symposium on Security & Privacy (S&P 2024)
pdf
Emiliano De Cristofaro
Synthetic Data: Methods, Use Cases, and Risks
IEEE Security and Privacy Magazine (Special Issue on Synthetic Realities), 2024
pdf
Meenatchi Sundaram Muthu Selva Annamalai, Igor Bilogrevic, Emiliano De Cristofaro
FP-Fed: Privacy-Preserving Federated Detection of Browser Fingerprinting
31st Network and Distributed System Security Symposium (NDSS 2024)
pdf
Wai Man Si, Jeremy Blackburn, Emiliano De Cristofaro, Gianluca Stringhini, Savvas Zannettou, Yang Zhang
Why So Toxic? Measuring and Triggering Toxic Behavior in Open-Domain Chatbots
29th ACM Conference on Computer and Communications Security (ACM CCS 2022)
honorable mention
pdf
media coverage FastCompany
Mohammad Naseri, Yufei Han, Enrico Mariconti, Yun Shen, Gianluca Stringhini, Emiliano De Cristofaro
CERBERUS: Exploring Federated Prediction of Security Events
29th ACM Conference on Computer and Communications Security (ACM CCS 2022)
pdf
Georgi Ganev, Bristena Oprisanu, Emiliano De Cristofaro
Robin Hood and Matthew Effects – Differential Privacy Has Disparate Impact on Synthetic Data
39th International Conference on Machine Learning (ICML 2022)
pdf
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)
pdf
Bristena Oprisanu, Georgi Ganev, Emiliano De Cristofaro
On Utility and Privacy in Synthetic Genomic Data
29th Network and Distributed System Security Symposium (NDSS 2022)
pdf
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)
pdf
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 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