Collecting Sensitive Data with Local Differential Privacy

Speaker:        Tianhao Wang
                Purdue University

Title:          "Collecting Sensitive Data with Local Differential
                 Privacy"

Date:           Tuesday, 9 February 2021

Time:           10am - 11am

Zoom Link:
https://hkust.zoom.us/j/465698645?pwd=c2E4VTE3b2lEYnBXcyt4VXJITXRIdz09

Meeting ID:     465 698 645
Passcode:       20202021

Abstract:

When collecting information, local differential privacy (LDP) relieves
users' privacy concerns, as it adds noise to users' private information.
The LDP technique has been deployed by Google, Apple, Microsoft, and
Alibaba for data collection. In this talk, I will share our research on
the basic primitives for LDP and a system that can handle analytical
queries under LDP.

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Biography:

Tianhao Wang is a Ph.D. candidate in the department of computer science,
Purdue University, advised by Prof. Ninghui Li. He received his B.Eng.
degree from software school, Fudan University in 2015. His research
interests include differential privacy and applied cryptography. He is a
member of DPSyn, which won the second-place award six times in
differential privacy competitions. He is a recipient of the Bilsland
Dissertation Fellowship and the Emil Stefanov Memorial Fellowship.