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Privacy-Preserving Record Linkage: Technological, Ethical, Adversarial, and Analytical Developments

Dinusha Vatsalan le

Lieu: bât 862, Amphis 33-34

Suivre en visio

Abstract

Personal Identifiable Information (PII) about individuals, such as customers, taxpayers, patients, and mobile application users, is increasingly collected and linked across disparate data sources to enable customized, high-quality, and timely analytical services in a variety of applications. Examples include health applications such as similar patient matching for clinical trials and rare disease patients counting for adequate awareness and funding, business applications that collect personal information to support customer contracts and improve business operations, governments services that collect personal data for national security and public safety, and cybersecurity applications such as tracking the number of unique views of social media posts. The data (PII) needed for the linkage analytics is, however, often personal and sensitive, and needs to be processed using privacy-preserving techniques. Known as privacy-preserving record linkage (PPRL), a large body of work has been conducted in this research topic. I have been conducting research and development in PPRL addressing the key challenges of enhancing computational efficiency, linkage quality, and privacy guarantees of linkage. In this talk, I will present our work on PPRL and an outlook to the next directions of research.