Technical Approaches to Measure and Mitigate Re-identification Risk… And Why They are Not Sufficient

Date: 

Fri Jun 20, 2014

Host: 

Bradley Malin
Vanderbilt University

Category: 

Privacy Technology

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ABSTRACT

One of the key protections associated with human subjects research settings is the “identifiability” of the participants.  This issue has moved to the forefront of the debate on human subjects protections as life science researchers evolve from small scale studies to “big data” investigations that incorporate an array resources ranging from longitudinal medical records to biorepositories.  In particular, there is concern that “de-identification” has become a myth, a belief that is due, in part, to an increasing number of detective-like attacks demonstrate that the identity of research participants can be compromised.  The goal of this talk is to review how such attacks transpire, how we can quantify them using computational and statistical strategies how to minimize such risks while maximizing the utility of the data.  At the same time, this talk will begin to address the challenges of relying solely on technical solutions and how a mix of socio-technical solutions may be designed to facilitate broader acceptance of quantified protections.

 

SPEAKER BIOGRAPHY

Bradley Malin, Ph.D. is an Associate Professor and Vice Chair of Biomedical Informatics in the School of Medicine, an Associate Professor of Computer Science in the School of Engineering, and Affiliated Faculty in the Center for Biomedical Ethics and Society at Vanderbilt University.  He founded and currently directs the Health Information Privacy Laboratory (HIPLab), which develops technologies that enable privacy in the context of real world organizational, political, and health information architectures.  From 2010-2013, he assisted the Office for Civil Rights at the U.S. Department of Health and Human Services in the development of guidance for de-identification in accordance the HIPAA Privacy Rule.  He is an elected fellow of the American College of Medical Informatics and a recipient of the Presidential Early Career Award for Scientists and Engineers (PECASE). He completed his education at Carnegie Mellon University, where he received a bachelor's in biology, master's in public policy and management, and doctorate in computer science.

 

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