134 citations · 212 across the 11 of their papers we have counts for
4 papers · 1 filter
Efficient Privacy-Preserving Retrieval Augmented Generation with Distance-Preserving Encryption
Huanyi Ye, Jiale Guo, Ziyao Liu +1
RAG has emerged as a key technique for enhancing response quality of LLMs without high computational cost. In traditional architectures, RAG services are provided by a single entit…
Efficient Federated Unlearning with Adaptive Differential Privacy Preservation
Yu Jiang, Xindi Tong, Ziyao Liu +3
Federated unlearning (FU) offers a promising solution to effectively address the need to erase the impact of specific clients' data on the global model in federated learning (FL),…
Efficient Dropout-resilient Aggregation for Privacy-preserving Machine Learning
Ziyao Liu, Jiale Guo, Kwok-Yan Lam +1
With the increasing adoption of data-hungry machine learning algorithms, personal data privacy has emerged as one of the key concerns that could hinder the success of digital trans…
MPC-enabled Privacy-Preserving Neural Network Training against Malicious Attack
Ziyao Liu, Ivan Tjuawinata, Chaoping Xing +1
The application of secure multiparty computation (MPC) in machine learning, especially privacy-preserving neural network training, has attracted tremendous attention from the resea…