Fang-Yu Rao - Purdue University
Students: Spring 2023, unless noted otherwise, sessions will be virtual on Zoom.
A Hybrid Private Record Linkage Scheme: Separating Differentially Private Synopses FromMatching Records
Oct 14, 2015Download: MP4 Video Size: 103.0MB
Watch on YouTube
AbstractPrivate record linkage protocols allow multiple parties to exchange matching records, which refer to the same entities or have similar values, while keeping the non-matching ones secret. Conventional protocols are based on computationally expensive cryptographic primitives and therefore do not scale. To address these scalability issues, hybrid protocols have been recently proposed that combine differential privacy techniques with secure multiparty computation techniques. However, a drawback of such protocols is that they disclose to the parties both the matching records and the differentially private synopses of the datasets involved in the linkage. Consequently, differential privacy is no longer always satisfied. To address this issue, we propose a novel framework, which separates the private synopses from the matching records. The two parties do not access the synopses directly, but still use them to efficiently link records. We theoretically prove the security of our framework. In addition, we have developed a simple but effective strategy for releasing private synopses. Extensive experimental results show that our framework is superior to the existing methods in terms of both recall rate and efficiency.
About the Speaker
Fang-Yu Rao is a Ph.D. candidate in Computer Science at Purdue University. He received his Master and Bachelor of Computer Science and Engineering from National Sun Yat-sen University. His research interests are in data privacy, information security, and applied cryptography, with an emphasis on privacy-preserving data analytics.