18 citations · 30 across the 9 of their papers we have counts for
7 papers · 1 filter
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…
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…
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…