Privacy Risks of Securing Machine Learning Models against Adversarial
Examples

Privacy Risks of Securing Machine Learning Models against Adversarial Examples

24 May 2019

Papers citing "Privacy Risks of Securing Machine Learning Models against Adversarial Examples"

15 / 15 papers shown

Title
AMUN: Adversarial Machine UNlearning A. Boroojeny Hari Sundaram Varun Chandrasekaran MU AAML 63 0 0 02 Mar 2025
Guarding the Privacy of Label-Only Access to Neural Network Classifiers via iDP Verification Anan Kabaha Dana Drachsler-Cohen AAML 62 0 0 23 Feb 2025
Rethinking Membership Inference Attacks Against Transfer Learning Yanwei Yue Jing Chen Qianru Fang Kun He Ziming Zhao Hao Ren Guowen Xu Yang Liu Yang Xiang 102 34 0 20 Jan 2025
FedQUIT: On-Device Federated Unlearning via a Quasi-Competent Virtual Teacher Alessio Mora Lorenzo Valerio Paolo Bellavista A. Passarella FedML MU 76 2 0 14 Aug 2024
Certified Adversarial Robustness via Randomized Smoothing Jeremy M. Cohen Elan Rosenfeld J. Zico Kolter AAML 111 2,018 0 08 Feb 2019
Improving the Generalization of Adversarial Training with Domain Adaptation Chuanbiao Song Kun He Liwei Wang John E. Hopcroft AAML OOD 72 131 0 01 Oct 2018
Manipulating Machine Learning: Poisoning Attacks and Countermeasures for Regression Learning Matthew Jagielski Alina Oprea Battista Biggio Chang-rui Liu Cristina Nita-Rotaru Yue Liu AAML 80 757 0 01 Apr 2018
On the Suitability of $L_p$ -norms for Creating and Preventing Adversarial Examples Mahmood Sharif Lujo Bauer Michael K. Reiter AAML 112 138 0 27 Feb 2018
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms Han Xiao Kashif Rasul Roland Vollgraf 196 8,807 0 25 Aug 2017
Evasion Attacks against Machine Learning at Test Time Battista Biggio Igino Corona Davide Maiorca B. Nelson Nedim Srndic Pavel Laskov Giorgio Giacinto Fabio Roli AAML 106 2,142 0 21 Aug 2017
Understanding Black-box Predictions via Influence Functions Pang Wei Koh Percy Liang TDI 144 2,854 0 14 Mar 2017
DeepStack: Expert-Level Artificial Intelligence in No-Limit Poker Matej Moravcík Martin Schmid Neil Burch Viliam Lisý Dustin Morrill Nolan Bard Trevor Davis Kevin Waugh Michael Bradley Johanson Michael Bowling BDL 111 905 0 06 Jan 2017
Membership Inference Attacks against Machine Learning Models Reza Shokri M. Stronati Congzheng Song Vitaly Shmatikov SLR MIALM MIACV 216 4,075 0 18 Oct 2016
Globally Normalized Transition-Based Neural Networks D. Andor Chris Alberti David J. Weiss Aliaksei Severyn Alessandro Presta Kuzman Ganchev Slav Petrov Michael Collins 82 568 0 19 Mar 2016
Poisoning Attacks against Support Vector Machines Battista Biggio B. Nelson Pavel Laskov AAML 99 1,580 0 27 Jun 2012