“What’s in the box?!”: Deflecting Adversarial Attacks by Randomly Deploying Adversarially-Disjoint Models
Authors: Sahar Abdelnabi, Mario Fritz | Published: 2021-02-09 | Updated: 2021-03-09
$k$-Anonymity in Practice: How Generalisation and Suppression Affect Machine Learning Classifiers
Authors: Djordje Slijepčević, Maximilian Henzl, Lukas Daniel Klausner, Tobias Dam, Peter Kieseberg, Matthias Zeppelzauer | Published: 2021-02-09 | Updated: 2022-06-22
Protecting Intellectual Property of Generative Adversarial Networks from Ambiguity Attack
Authors: Ding Sheng Ong, Chee Seng Chan, Kam Woh Ng, Lixin Fan, Qiang Yang | Published: 2021-02-08 | Updated: 2021-03-01
Efficient Certified Defenses Against Patch Attacks on Image Classifiers
Authors: Jan Hendrik Metzen, Maksym Yatsura | Published: 2021-02-08
Quantifying and Mitigating Privacy Risks of Contrastive Learning
Authors: Xinlei He, Yang Zhang | Published: 2021-02-08 | Updated: 2021-09-21
Optimal Transport as a Defense Against Adversarial Attacks
Authors: Quentin Bouniot, Romaric Audigier, Angélique Loesch | Published: 2021-02-05 | Updated: 2021-03-30
ML-Doctor: Holistic Risk Assessment of Inference Attacks Against Machine Learning Models
Authors: Yugeng Liu, Rui Wen, Xinlei He, Ahmed Salem, Zhikun Zhang, Michael Backes, Emiliano De Cristofaro, Mario Fritz, Yang Zhang | Published: 2021-02-04 | Updated: 2021-10-06
Adversarially Robust Learning with Unknown Perturbation Sets
Authors: Omar Montasser, Steve Hanneke, Nathan Srebro | Published: 2021-02-03
TAD: Trigger Approximation based Black-box Trojan Detection for AI
Authors: Xinqiao Zhang, Huili Chen, Farinaz Koushanfar | Published: 2021-02-03 | Updated: 2021-04-20
Symmetric Sparse Boolean Matrix Factorization and Applications
Authors: Sitan Chen, Zhao Song, Runzhou Tao, Ruizhe Zhang | Published: 2021-02-02 | Updated: 2022-01-13