Sponge Examples: Energy-Latency Attacks on Neural Networks
Authors: Ilia Shumailov, Yiren Zhao, Daniel Bates, Nicolas Papernot, Robert Mullins, Ross Anderson | Published: 2020-06-05 | Updated: 2021-05-12
Membership Inference
An Overview of Privacy in Machine Learning
Authors: Emiliano De Cristofaro | Published: 2020-05-18
Perturbing Inputs to Prevent Model Stealing
Authors: Justin Grana | Published: 2020-05-12
When Machine Unlearning Jeopardizes Privacy
Authors: Min Chen, Zhikun Zhang, Tianhao Wang, Michael Backes, Mathias Humbert, Yang Zhang | Published: 2020-05-05 | Updated: 2021-09-14
Private Dataset Generation Using Privacy Preserving Collaborative Learning
Authors: Amit Chaulwar | Published: 2020-04-28
Privacy in Deep Learning: A Survey
Authors: Fatemehsadat Mireshghallah, Mohammadkazem Taram, Praneeth Vepakomma, Abhishek Singh, Ramesh Raskar, Hadi Esmaeilzadeh | Published: 2020-04-25 | Updated: 2020-11-07
Information Leakage in Embedding Models
Authors: Congzheng Song, Ananth Raghunathan | Published: 2020-03-31 | Updated: 2020-08-19
Systematic Evaluation of Privacy Risks of Machine Learning Models
Authors: Liwei Song, Prateek Mittal | Published: 2020-03-24 | Updated: 2020-12-09
Adversarial Machine Learning — Industry Perspectives
Authors: Ram Shankar Siva Kumar, Magnus Nyström, John Lambert, Andrew Marshall, Mario Goertzel, Andi Comissoneru, Matt Swann, Sharon Xia | Published: 2020-02-04 | Updated: 2021-03-19
Politics of Adversarial Machine Learning
Authors: Kendra Albert, Jonathon Penney, Bruce Schneier, Ram Shankar Siva Kumar | Published: 2020-02-01 | Updated: 2020-04-26