A Comprehensive Study of Privacy Risks in Curriculum Learning
Authors: Joann Qiongna Chen, Xinlei He, Zheng Li, Yang Zhang, Zhou Li | Published: 2023-10-16
Membership Inference
Why Train More? Effective and Efficient Membership Inference via Memorization
Authors: Jihye Choi, Shruti Tople, Varun Chandrasekaran, Somesh Jha | Published: 2023-10-12
Text Embeddings Reveal (Almost) As Much As Text
Authors: John X. Morris, Volodymyr Kuleshov, Vitaly Shmatikov, Alexander M. Rush | Published: 2023-10-10
Vulnerability Clustering and other Machine Learning Applications of Semantic Vulnerability Embeddings
Authors: Mark-Oliver Stehr, Minyoung Kim | Published: 2023-08-23
Security and Privacy Issues of Federated Learning
Authors: Jahid Hasan | Published: 2023-07-22
A LLM Assisted Exploitation of AI-Guardian
Authors: Nicholas Carlini | Published: 2023-07-20
Eliminating Label Leakage in Tree-Based Vertical Federated Learning
Authors: Hideaki Takahashi, Jingjing Liu, Yang Liu | Published: 2023-07-19 | Updated: 2023-10-22
Privacy-Preserving Graph Machine Learning from Data to Computation: A Survey
Authors: Dongqi Fu, Wenxuan Bao, Ross Maciejewski, Hanghang Tong, Jingrui He | Published: 2023-07-10
Overconfidence is a Dangerous Thing: Mitigating Membership Inference Attacks by Enforcing Less Confident Prediction
Authors: Zitao Chen, Karthik Pattabiraman | Published: 2023-07-04
You Don’t Need Robust Machine Learning to Manage Adversarial Attack Risks
Authors: Edward Raff, Michel Benaroch, Andrew L. Farris | Published: 2023-06-16