FairDP: Certified Fairness with Differential Privacy

no code implementations • 25 May 2023 • Khang Tran, Ferdinando Fioretto, Issa Khalil, My T. Thai, NhatHai Phan

This paper introduces FairDP, a novel mechanism designed to achieve certified fairness with differential privacy (DP).

Fairness

Active Membership Inference Attack under Local Differential Privacy in Federated Learning

1 code implementation • 24 Feb 2023 • Truc Nguyen, Phung Lai, Khang Tran, NhatHai Phan, My T. Thai

Federated learning (FL) was originally regarded as a framework for collaborative learning among clients with data privacy protection through a coordinating server.

Federated Learning Inference Attack +2

Heterogeneous Randomized Response for Differential Privacy in Graph Neural Networks

1 code implementation • 10 Nov 2022 • Khang Tran, Phung Lai, NhatHai Phan, Issa Khalil, Yao Ma, Abdallah Khreishah, My Thai, Xintao Wu

Graph neural networks (GNNs) are susceptible to privacy inference attacks (PIAs), given their ability to learn joint representation from features and edges among nodes in graph data.