15 citations · 50 across the 24 of their papers we have counts for
3 papers · 1 filter
SoK: Let the Privacy Games Begin! A Unified Treatment of Data Inference Privacy in Machine Learning
Ahmed Salem, Giovanni Cherubin, David Evans +5
Deploying machine learning models in production may allow adversaries to infer sensitive information about training data. There is a vast literature analyzing different types of in…
Dissecting Distribution Inference
Anshuman Suri, Yifu Lu, Yanjin Chen +1
A distribution inference attack aims to infer statistical properties of data used to train machine learning models. These attacks are sometimes surprisingly potent, but the factors…
Subject Membership Inference Attacks in Federated Learning
Anshuman Suri, Pallika Kanani, Virendra J. Marathe +1
Privacy attacks on Machine Learning (ML) models often focus on inferring the existence of particular data points in the training data. However, what the adversary really wants to k…