26 citations · 96 across the 33 of their papers we have counts for
5 papers · 1 filter
XRand: Differentially Private Defense against Explanation-Guided Attacks
Truc Nguyen, Phung Lai, NhatHai Phan +1
Recent development in the field of explainable artificial intelligence (XAI) has helped improve trust in Machine-Learning-as-a-Service (MLaaS) systems, in which an explanation is p…
Heterogeneous Randomized Response for Differential Privacy in Graph Neural Networks
Khang Tran, Phung Lai, NhatHai Phan +5
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 dat…
User-Entity Differential Privacy in Learning Natural Language Models
Phung Lai, NhatHai Phan, Tong Sun +4
In this paper, we introduce a novel concept of user-entity differential privacy (UeDP) to provide formal privacy protection simultaneously to both sensitive entities in textual dat…
Lifelong DP: Consistently Bounded Differential Privacy in Lifelong Machine Learning
Phung Lai, Han Hu, NhatHai Phan +3
In this paper, we show that the process of continually learning new tasks and memorizing previous tasks introduces unknown privacy risks and challenges to bound the privacy loss. B…
How to Backdoor HyperNetwork in Personalized Federated Learning?
Phung Lai, NhatHai Phan, Issa Khalil +2
This paper explores previously unknown backdoor risks in HyperNet-based personalized federated learning (HyperNetFL) through poisoning attacks. Based upon that, we propose a novel…