7 citations · 19 across the 13 of their papers we have counts for
9 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),…
Guaranteeing Data Privacy in Federated Unlearning with Dynamic User Participation
Ziyao Liu, Yu Jiang, Weifeng Jiang +3
Federated Unlearning (FU) is gaining prominence for its capability to eliminate influences of Federated Learning (FL) users' data from trained global FL models. A straightforward F…
Privacy-Preserving Federated Unlearning with Certified Client Removal
Ziyao Liu, Huanyi Ye, Yu Jiang +4
In recent years, Federated Unlearning (FU) has gained attention for addressing the removal of a client's influence from the global model in Federated Learning (FL) systems, thereby…
Threats, Attacks, and Defenses in Machine Unlearning: A Survey
Ziyao Liu, Huanyi Ye, Chen Chen +2
Machine Unlearning (MU) has recently gained considerable attention due to its potential to achieve Safe AI by removing the influence of specific data from trained Machine Learning…
Effective Intrusion Detection in Heterogeneous Internet-of-Things Networks via Ensemble Knowledge Distillation-based Federated Learning
Jiyuan Shen, Wenzhuo Yang, Zhaowei Chu +3
With the rapid development of low-cost consumer electronics and cloud computing, Internet-of-Things (IoT) devices are widely adopted for supporting next-generation distributed syst…