193 citations · 591 across the 14 of their papers we have counts for
3 papers · 1 filter
A Hybrid Approach to Privacy-Preserving Federated Learning
Stacey Truex, Nathalie Baracaldo, Ali Anwar +4
Federated learning facilitates the collaborative training of models without the sharing of raw data. However, recent attacks demonstrate that simply maintaining data locality durin…
Towards Demystifying Membership Inference Attacks
Stacey Truex, Ling Liu, Mehmet Emre Gursoy +2
Membership inference attacks seek to infer membership of individual training instances of a model to which an adversary has black-box access through a machine learning-as-a-service…
Adversarial Examples in Deep Learning: Characterization and Divergence
Wenqi Wei, Ling Liu, Margaret Loper +4
The burgeoning success of deep learning has raised the security and privacy concerns as more and more tasks are accompanied with sensitive data. Adversarial attacks in deep learnin…