Truth Serum: Poisoning Machine Learning Models to Reveal Their Secrets
Authors: Florian Tramèr, Reza Shokri, Ayrton San Joaquin, Hoang Le, Matthew Jagielski, Sanghyun Hong, Nicholas Carlini | Published: 2022-03-31 | Updated: 2022-10-06
Privacy Assessment
Differentially Private Federated Learning via Reconfigurable Intelligent Surface
Authors: Yuhan Yang, Yong Zhou, Youlong Wu, Yuanming Shi | Published: 2022-03-31
Privacy-Preserving Reinforcement Learning Beyond Expectation
Authors: Arezoo Rajabi, Bhaskar Ramasubramanian, Abdullah Al Maruf, Radha Poovendran | Published: 2022-03-18
Evaluating Privacy-Preserving Machine Learning in Critical Infrastructures: A Case Study on Time-Series Classification
Authors: Dominique Mercier, Adriano Lucieri, Mohsin Munir, Andreas Dengel, Sheraz Ahmed | Published: 2021-11-29
Statistical Privacy Guarantees of Machine Learning Preprocessing Techniques
Authors: Ashly Lau, Jonathan Passerat-Palmbach | Published: 2021-09-06
Private Multi-Task Learning: Formulation and Applications to Federated Learning
Authors: Shengyuan Hu, Zhiwei Steven Wu, Virginia Smith | Published: 2021-08-30 | Updated: 2023-10-17
Mitigating Statistical Bias within Differentially Private Synthetic Data
Authors: Sahra Ghalebikesabi, Harrison Wilde, Jack Jewson, Arnaud Doucet, Sebastian Vollmer, Chris Holmes | Published: 2021-08-24 | Updated: 2022-05-19
Privacy-Preserving Machine Learning: Methods, Challenges and Directions
Authors: Runhua Xu, Nathalie Baracaldo, James Joshi | Published: 2021-08-10 | Updated: 2021-09-22
Every Query Counts: Analyzing the Privacy Loss of Exploratory Data Analyses
Authors: Saskia Nuñez von Voigt, Mira Pauli, Johanna Reichert, Florian Tschorsch | Published: 2020-08-27
Deep Active Learning with Crowdsourcing Data for Privacy Policy Classification
Authors: Wenjun Qiu, David Lie | Published: 2020-08-07