Privacy-Preserving Data Mining for Wearable Devices

Yanchao Zhang | School of Electrical, Computer and Energy Engineering

Wearable devices such as fitness and performance tracking gadgets are quickly penetrating into everyday life and transforming how people live. There are growing privacy concerns that fine-grained big data from wearables can be misused. This project is to investigate privacy-preserving data mining techniques for wearable devices. In the one-year project period, we will focus on distributed stream monitoring, an important data mining technique that monitors functions over distributed and continuous data streams in real-time. Our target system aims to provide accurate data with high communication efficiency and also strong privacy guarantees.

Published Work

PriStream: Privacy-Preserving Distributed Stream Monitoring of Thresholded Percentile Statistics

Last updated March 2020.