808 citations · 1.1k across the 21 of their papers we have counts for
3 papers · 1 filter
Blind Backdoors in Deep Learning Models
Eugene Bagdasaryan, Vitaly Shmatikov
We investigate a new method for injecting backdoors into machine learning models, based on compromising the loss-value computation in the model-training code. We use it to demonstr…
Policy-Based Federated Learning
Kleomenis Katevas, Eugene Bagdasaryan, Jason Waterman +4
In this paper we present PoliFL, a decentralized, edge-based framework that supports heterogeneous privacy policies for federated learning. We evaluate our system on three use case…
Salvaging Federated Learning by Local Adaptation
Tao Yu, Eugene Bagdasaryan, Vitaly Shmatikov
Federated learning (FL) is a heavily promoted approach for training ML models on sensitive data, e.g., text typed by users on their smartphones. FL is expressly designed for traini…