Privacy-Preserving Data Publishing

Benjamin Fung
Simon Fraser University

Monday, April 9, 11:00AM
Babbio Center, Room 202
Stevens Institute of Technology
 

Abstract


The success of data mining relies on the availability of high quality data. To ensure quality data mining, effective information sharing between organizations becomes a vital requirement in today's society. Since data mining often involves person-specific and sensitive information like medical records, the public acquires a negative impression that data mining is a tool for privacy intrusion. Privacy-preserving data publishing is a study of eliminating privacy threats while, at the same time, preserving useful structures in the released data for data mining. This talk studies a collection of privacy threats in real life data publishing, and presents a unified solution to address these threats.