A Note On Interpreting Canary Exposure
Authors: Matthew Jagielski | Published: 2023-05-31 | Updated: 2023-06-02
Membership Inference
Blockchain Large Language Models
Authors: Yu Gai, Liyi Zhou, Kaihua Qin, Dawn Song, Arthur Gervais | Published: 2023-04-25 | Updated: 2023-04-29
Identifying Appropriate Intellectual Property Protection Mechanisms for Machine Learning Models: A Systematization of Watermarking, Fingerprinting, Model Access, and Attacks
Authors: Isabell Lederer, Rudolf Mayer, Andreas Rauber | Published: 2023-04-22
DRSM: De-Randomized Smoothing on Malware Classifier Providing Certified Robustness
Authors: Shoumik Saha, Wenxiao Wang, Yigitcan Kaya, Soheil Feizi, Tudor Dumitras | Published: 2023-03-20 | Updated: 2023-10-03
Mithridates: Auditing and Boosting Backdoor Resistance of Machine Learning Pipelines
Authors: Eugene Bagdasaryan, Vitaly Shmatikov | Published: 2023-02-09 | Updated: 2023-12-19
Threats, Vulnerabilities, and Controls of Machine Learning Based Systems: A Survey and Taxonomy
Authors: Yusuke Kawamoto, Kazumasa Miyake, Koichi Konishi, Yutaka Oiwa | Published: 2023-01-18 | Updated: 2023-01-19
Introducing Model Inversion Attacks on Automatic Speaker Recognition
Authors: Karla Pizzi, Franziska Boenisch, Ugur Sahin, Konstantin Böttinger | Published: 2023-01-09
SoK: Let the Privacy Games Begin! A Unified Treatment of Data Inference Privacy in Machine Learning
Authors: Ahmed Salem, Giovanni Cherubin, David Evans, Boris Köpf, Andrew Paverd, Anshuman Suri, Shruti Tople, Santiago Zanella-Béguelin | Published: 2022-12-21 | Updated: 2023-04-20
Dissecting Distribution Inference
Authors: Anshuman Suri, Yifu Lu, Yanjin Chen, David Evans | Published: 2022-12-15 | Updated: 2024-04-05
Amplifying Membership Exposure via Data Poisoning
Authors: Yufei Chen, Chao Shen, Yun Shen, Cong Wang, Yang Zhang | Published: 2022-11-01