1 citations · 1 across the 10 of their papers we have counts for
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Hoss: Fast Oblivious Semantic Search with Heterogeneous GPU-CPU-TEE Architecture
Jianzhang Du, Weijie Huang, Chenghong Wang +4
Semantic search is widely deployed in modern AI systems, but protecting both data contents and access patterns remains challenging. The current state-of-the-art system, Compass, ac…
Secret-Protected Evolution for Differentially Private Synthetic Text Generation
Tianze Wang, Zhaoyu Chen, Jian Du +3
Text data has become extremely valuable on large language models (LLMs) and even lead to general artificial intelligence (AGI). A lot of high-quality text in the real world is priv…
PrivacyGo: Privacy-Preserving Ad Measurement with Multidimensional Intersection
Jian Du, Haohao Qian, Shikun Zhang +6
This paper tackles the challenging and practical problem of multi-identifier private user profile matching for privacy-preserving ad measurement, a cornerstone of modern advertisin…
When Focus Enhances Utility: Target Range LDP Frequency Estimation and Unknown Item Discovery
Bo Jiang, Wanrong Zhang, Donghang Lu +2
Local Differential Privacy (LDP) protocols enable the collection of randomized client messages for data analysis, without the necessity of a trusted data curator. Such protocols ha…
Meeting Utility Constraints in Differential Privacy: A Privacy-Boosting Approach
Bo Jiang, Wanrong Zhang, Donghang Lu +3
Data engineering often requires accuracy (utility) constraints on results, posing significant challenges in designing differentially private (DP) mechanisms, particularly under str…
Click Without Compromise: Online Advertising Measurement via Per User Differential Privacy
Yingtai Xiao, Jian Du, Shikun Zhang +4
Online advertising is a cornerstone of the Internet ecosystem, with advertising measurement playing a crucial role in optimizing efficiency. Ad measurement entails attributing desi…
Budget Recycling Differential Privacy
Bo Jiang, Jian Du, Sagar Sharma +1
Differential Privacy (DP) mechanisms usually {force} reduction in data utility by producing "out-of-bound" noisy results for a tight privacy budget. We introduce the Budget Recycli…
AnonPSI: An Anonymity Assessment Framework for PSI
Bo Jiang, Jian Du, Qiang Yan
Private Set Intersection (PSI) is a widely used protocol that enables two parties to securely compute a function over the intersected part of their shared datasets and has been a s…