A Framework for Evaluating Gradient Leakage Attacks in Federated Learning

2 code implementations • 22 Apr 2020 • Wenqi Wei, Ling Liu, Margaret Loper, Ka-Ho Chow, Mehmet Emre Gursoy, Stacey Truex, Yanzhao Wu

FL offers default client privacy by allowing clients to keep their sensitive data on local devices and to only share local training parameter updates with the federated server.

Federated Learning

Cross-Layer Strategic Ensemble Defense Against Adversarial Examples

no code implementations • 1 Oct 2019 • Wenqi Wei, Ling Liu, Margaret Loper, Ka-Ho Chow, Emre Gursoy, Stacey Truex, Yanzhao Wu

Deep neural network (DNN) has demonstrated its success in multiple domains.

Deep Neural Network Ensembles against Deception: Ensemble Diversity, Accuracy and Robustness

no code implementations • 29 Aug 2019 • Ling Liu, Wenqi Wei, Ka-Ho Chow, Margaret Loper, Emre Gursoy, Stacey Truex, Yanzhao Wu

In this paper we first give an overview of the concept of ensemble diversity and examine the three types of ensemble diversity in the context of DNN classifiers.

Ensemble Learning

Adversarial Examples in Deep Learning: Characterization and Divergence

no code implementations • 29 Jun 2018 • Wenqi Wei, Ling Liu, Margaret Loper, Stacey Truex, Lei Yu, Mehmet Emre Gursoy, Yanzhao Wu

The burgeoning success of deep learning has raised the security and privacy concerns as more and more tasks are accompanied with sensitive data.

Adversarial Attack