2 citations · 4 across the 7 of their papers we have counts for
7 papers
Toward Efficient Membership Inference Attacks against Federated Large Language Models: A Projection Residual Approach
Guilin Deng, Silong Chen, Yuchuan Luo +6
Federated Large Language Models (FedLLMs) enable multiple parties to collaboratively fine-tune LLMs without sharing raw data, addressing challenges of limited resources and privacy…
ObliuSky: Oblivious User-Defined Skyline Query Processing in the Cloud
Yifeng Zheng, Weibo Wang, Songlei Wang +2
The proliferation of cloud computing has greatly spurred the popularity of outsourced database storage and management, in which the cloud holding outsourced databases can process d…
Privet: A Privacy-Preserving Vertical Federated Learning Service for Gradient Boosted Decision Tables
Yifeng Zheng, Shuangqing Xu, Songlei Wang +2
Vertical federated learning (VFL) has recently emerged as an appealing distributed paradigm empowering multi-party collaboration for training high-quality models over vertically pa…
OblivGM: Oblivious Attributed Subgraph Matching as a Cloud Service
Songlei Wang, Yifeng Zheng, Xiaohua Jia +2
In recent years there has been growing popularity of leveraging cloud computing for storing and querying attributed graphs, which have been widely used to model complex structured…
SecSkyline: Fast Privacy-Preserving Skyline Queries over Encrypted Cloud Databases
Yifeng Zheng, Weibo Wang, Songlei Wang +3
The well-known benefits of cloud computing have spurred the popularity of database service outsourcing, where one can resort to the cloud to conveniently store and query databases.…
Privacy-Preserving Analytics on Decentralized Social Graphs: The Case of Eigendecomposition
Songlei Wang, Yifeng Zheng, Xiaohua Jia +1
Analytics over social graphs allows to extract valuable knowledge and insights for many fields like community detection, fraud detection, and interest mining. In practice, decentra…
SecGNN: Privacy-Preserving Graph Neural Network Training and Inference as a Cloud Service
Songlei Wang, Yifeng Zheng, Xiaohua Jia
Graphs are widely used to model the complex relationships among entities. As a powerful tool for graph analytics, graph neural networks (GNNs) have recently gained wide attention d…