Title：Data Distillation at the Edge: Local Differential Privacy Obfuscation for IoT Data Analytics

Abstract

Edge computing serves as a promising paradigm for IoT data analytics by shifting the data processing from the cloud to the edge. While the conventional approaches such as homomorphic encryption on the edge lead to inefficiency, how to preserve data privacy without sacrificing data utility is a challenging problem for IoT data analytics. In this talk, we introduce local differential privacy as a technique to strike a balance between data privacy and utility. Moreover, we will also present the recent research effort toward this research direction.

Author Biography

Chia-Mu Yu is currently an Assistant Professor and Hwa Tse Roger Liang Junior Chair Professor at National Chiao Tung University, Taiwan. He was a postdoc researcher at IBM Thomas J. Watson Research Center. He was a visiting scholar at Harvard University, Imperial College London, University of Padova, and the University of Illinois at Chicago. He received Young Scholar Fellowship from Ministry of Science and Technology, K. T. Li Young Researcher Award from ACM/IICM, Observational Research Scholarship from Pan Wen Yuan Foundation, and Project for Excellent Junior Research Investigators from the Ministry of Science and Technology, Taiwan. He was a Junior Distinguished Professor at National Chung Hsing University. His research interests include differentially private mechanism design, cloud storage security, and IoT security.