165 citations · 308 across the 13 of their papers we have counts for
13 papers
Theoretically Unmasking Inference Attacks Against LDP-Protected Clients in Federated Vision Models
Quan Nguyen, Minh N. Vu, Truc Nguyen +1
Federated Learning enables collaborative learning among clients via a coordinating server while avoiding direct data sharing, offering a perceived solution to preserve privacy. How…
Analysis of Privacy Leakage in Federated Large Language Models
Minh N. Vu, Truc Nguyen, Tre' R. Jeter +1
With the rapid adoption of Federated Learning (FL) as the training and tuning protocol for applications utilizing Large Language Models (LLMs), recent research highlights the need…
OASIS: Offsetting Active Reconstruction Attacks in Federated Learning
Tre' R. Jeter, Truc Nguyen, Raed Alharbi +1
Federated Learning (FL) has garnered significant attention for its potential to protect user privacy while enhancing model training efficiency. For that reason, FL has found its us…
Active Membership Inference Attack under Local Differential Privacy in Federated Learning
Truc Nguyen, Phung Lai, Khang Tran +2
Federated learning (FL) was originally regarded as a framework for collaborative learning among clients with data privacy protection through a coordinating server. In this paper, w…
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…
NeuCEPT: Locally Discover Neural Networks' Mechanism via Critical Neurons Identification with Precision Guarantee
Minh N. Vu, Truc D. Nguyen, My T. Thai
Despite recent studies on understanding deep neural networks (DNNs), there exists numerous questions on how DNNs generate their predictions. Especially, given similar predictions o…
Blockchain-based Secure Client Selection in Federated Learning
Truc Nguyen, Phuc Thai, Tre' R. Jeter +2
Despite the great potential of Federated Learning (FL) in large-scale distributed learning, the current system is still subject to several privacy issues due to the fact that local…
Preserving Privacy and Security in Federated Learning
Truc Nguyen, My T. Thai
Federated learning is known to be vulnerable to both security and privacy issues. Existing research has focused either on preventing poisoning attacks from users or on concealing t…
A Blockchain-based Iterative Double Auction Protocol using Multiparty State Channels
Truc D. T. Nguyen, My T. Thai
Although the iterative double auction has been widely used in many different applications, one of the major problems in its current implementations is that they rely on a trusted t…
Denial-of-Service Vulnerability of Hash-based Transaction Sharding: Attack and Countermeasure
Truc Nguyen, My T. Thai
Since 2016, sharding has become an auspicious solution to tackle the scalability issue in legacy blockchain systems. Despite its potential to strongly boost the blockchain throughp…
OptChain: Optimal Transactions Placement for Scalable Blockchain Sharding
Lan N. Nguyen, Truc Nguyen, Thang N. Dinh +1
A major challenge in blockchain sharding protocols is that more than 95% transactions are cross-shard. Not only those cross-shard transactions degrade the system throughput but als…
c-Eval: A Unified Metric to Evaluate Feature-based Explanations via Perturbation
Minh N. Vu, Truc D. Nguyen, NhatHai Phan +2
In many modern image-classification applications, understanding the cause of model's prediction can be as critical as the prediction's accuracy itself. Various feature-based local…
Publish-Subscribe Framework for Event Management in IoT-based Applications
Truc D. T. Nguyen, Quan M. B. Nguyen, Hoang-Anh Pham
The incredible growth of sensors and microcontroller units makes the task of real-time event monitoring in the Internet of Things (IoT) based applications easier and more practical…