225 citations · 805 across the 24 of their papers we have counts for
6 papers · 2 filters
Effects of Differential Privacy and Data Skewness on Membership Inference Vulnerability
Stacey Truex, Ling Liu, Mehmet Emre Gursoy +2
Membership inference attacks seek to infer the membership of individual training instances of a privately trained model. This paper presents a membership privacy analysis and evalu…
Utility-aware and privacy-preserving mobile query services
Emre Yigitoglu, Mehmet Emre Gursoy, Ling Liu
Location-based queries enable fundamental services for mobile road network travelers. While the benefits of location-based services (LBS) are numerous, exposure of mobile travelers…
StackVault: Protection from Untrusted Functions
Qi Zhang, Zehra Sura, Ashish Kundu +3
Data exfiltration attacks have led to huge data breaches. Recently, the Equifax attack affected 147M users and a third-party library - Apache Struts - was alleged to be responsible…
Secure and Utility-Aware Data Collection with Condensed Local Differential Privacy
Mehmet Emre Gursoy, Acar Tamersoy, Stacey Truex +2
Local Differential Privacy (LDP) is popularly used in practice for privacy-preserving data collection. Although existing LDP protocols offer high utility for large user populations…
Differentially Private Model Publishing for Deep Learning
Lei Yu, Ling Liu, Calton Pu +2
Deep learning techniques based on neural networks have shown significant success in a wide range of AI tasks. Large-scale training datasets are one of the critical factors for thei…
Security and Privacy on Blockchain
Rui Zhang, Rui Xue, Ling Liu
Blockchain offers an innovative approach to storing information, executing transactions, performing functions, and establishing trust in an open environment. Many consider blockcha…