Private Dataset Generation Using Privacy Preserving Collaborative Learning
Authors: Amit Chaulwar | Published: 2020-04-28
Membership Inference
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
Modelling and Quantifying Membership Information Leakage in Machine Learning
Authors: Farhad Farokhi, Mohamed Ali Kaafar | Published: 2020-01-29 | Updated: 2020-04-28
Humpty Dumpty: Controlling Word Meanings via Corpus Poisoning
Authors: Roei Schuster, Tal Schuster, Yoav Meri, Vitaly Shmatikov | Published: 2020-01-14
Membership Inference Attacks Against Object Detection Models
Authors: Yeachan Park, Myungjoo Kang | Published: 2020-01-12 | Updated: 2020-01-28
To Transfer or Not to Transfer: Misclassification Attacks Against Transfer Learned Text Classifiers
Authors: Bijeeta Pal, Shruti Tople | Published: 2020-01-08