5 papers
Context-Aware Metric Differential Privacy for Vehicle Trajectory Data
Gaoyi Chen, Yan Huang, Chenxi Qiu
Metric Differential Privacy (mDP) generalizes differential privacy by allowing privacy guarantees to be expressed with respect to an arbitrary distance metric over secrets. While m…
Metric-Normalized Posterior Leakage (mPL): Attacker-Aligned Privacy for Joint Consumption
Gaoyi Chen, Minghao Li, Weishi Shi +4
Metric differential privacy (mDP) strengthens local differential privacy (LDP) by scaling noise to semantic distance, but many machine learning (ML) systems are consumed under join…
FUSE-Traffic: Fusion of Unstructured and Structured Data for Event-aware Traffic Forecasting
Chenyang Yu, Xinpeng Xie, Yan Huang +1
Accurate traffic forecasting is a core technology for building Intelligent Transportation Systems (ITS), enabling better urban resource allocation and improved travel experiences.…
A Decade of Metric Differential Privacy: Advancements and Applications
Xinpeng Xie, Chenyang Yu, Yan Huang +2
Metric Differential Privacy (mDP) builds upon the core principles of Differential Privacy (DP) by incorporating various distance metrics, which offer adaptable and context-sensitiv…
FlowDistill: Scalable Traffic Flow Prediction via Distillation from LLMs
Chenyang Yu, Xinpeng Xie, Yan Huang +1
Accurate traffic flow prediction is vital for optimizing urban mobility, yet it remains difficult in many cities due to complex spatio-temporal dependencies and limited high-qualit…