2 papers
cs.CR2022
Privacy-preserving Decentralized Federated Learning over Time-varying Communication Graph
Yang Lu, Zhengxin Yu, Neeraj Suri
Establishing how a set of learners can provide privacy-preserving federated learning in a fully decentralized (peer-to-peer, no coordinator) manner is an open problem. We propose t…
cs.CR2022
PINCH: An Adversarial Extraction Attack Framework for Deep Learning Models
William Hackett, Stefan Trawicki, Zhengxin Yu +2
Adversarial extraction attacks constitute an insidious threat against Deep Learning (DL) models in-which an adversary aims to steal the architecture, parameters, and hyper-paramete…