6 papers
AudAgent: Automated Auditing of Privacy Policy Compliance in AI Agents
Ye Zheng, Yimin Chen, Yidan Hu
AI agents can autonomously perform tasks and, often without explicit user consent, collect or disclose users' sensitive local data, which raises serious privacy concerns. Although…
TraCS: Trajectory Collection in Continuous Space under Local Differential Privacy
Ye Zheng, Yidan Hu
Trajectory collection is essential for location-based services, yet it can reveal highly sensitive information about users, such as daily routines and activities, raising serious p…
Quantifying Classifier Utility under Local Differential Privacy
Ye Zheng, Yidan Hu
Local differential privacy (LDP) offers rigorous, quantifiable privacy guarantees for personal data by introducing perturbations at the data source. Understanding how these perturb…
Frequency Estimation of Correlated Multi-attribute Data under Local Differential Privacy
Shafizur Rahman Seeam, Ye Zheng, Yidan Hu
Large-scale data collection, from national censuses to IoT-enabled smart homes, routinely gathers dozens of attributes per individual. These multi-attribute datasets are crucial fo…
PrivAR: Client-Side Privacy Framework for Real-Time Location-Based Augmented Reality
Shafizur Rahman Seeam, Ye Zheng, Zhengxiong Li +1
Location-based augmented reality (LB-AR) applications, such as Pokemon Go, rely on sub-second GPS updates to deliver responsive and immersive user experiences. However, this high-f…
Optimal Piecewise-based Mechanism for Collecting Bounded Numerical Data under Local Differential Privacy
Ye Zheng, Sumita Mishra, Yidan Hu
Numerical data with bounded domains is a common data type in personal devices, such as wearable sensors. While the collection of such data is essential for third-party platforms, i…