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Arvind Narayanan

Publications and source records attributed to Arvind Narayanan.

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Redefining Genomic Privacy: Trust and Empowerment

Fulfilling the promise of the genetic revolution requires the analysis of large datasets containing information from thousands to millions of participants. However, sharing human genomic data requires protecting subjects from potential harm. Current models rely on de-identification techniques that treat privacy versus data utility as a zero-sum game. Instead we propose using trust-enabling techniques to create a solution where researchers and participants both win. To do so we introduce three principles that facilitate trust in genetic research and outline one possible framework built upon those principles. Our hope is that such trust-centric frameworks provide a sustainable solution that reconciles genetic privacy with data sharing and facilitates genetic research.

Genomics

Routes for breaching and protecting genetic privacy

We are entering the era of ubiquitous genetic information for research, clinical care, and personal curiosity. Sharing these datasets is vital for rapid progress in understanding the genetic basis of human diseases. However, one growing concern is the ability to protect the genetic privacy of the data originators. Here, we technically map threats to genetic privacy and discuss potential mitigation strategies for privacy-preserving dissemination of genetic data.\n\nAbout the AuthorsYaniv Erlich is a Fellow at the Whitehead Institute for Biomedical Research. Erlich received his Ph.D. from Cold Spring Harbor Laboratory in 2010 and B.Sc. from Tel-Aviv University in 2006. Prior to that, Erlich worked in computer security and was responsible for conducting penetration tests on financial institutes and commercial companies. Dr. Erlichs research involves developing new algorithms for computational human genetics.\n\nArvind Narayanan is an Assistant Professor in the Department of Computer Science and the Center for Information Technology and Policy at Princeton. He studies information privacy and security. His research has shown that data anonymization is broken in fundamental ways, for which he jointly received the 2008 Privacy Enhancing Technologies Award. His current research interests include building a platform for privacy-preserving data sharing.\n\nSummaryO_LIBroad data dissemination is essential for advancements in genetics, but also brings to light concerns regarding privacy.\nC_LIO_LIPrivacy breaching techniques work by cross-referencing two or more pieces of information to gain new, potentially undesirable knowledge on individuals or their families.\nC_LIO_LIBroadly speaking, the main routes to breach privacy are identity tracing, attribute disclosure, and completion of sensitive DNA information.\nC_LIO_LIIdentity tracing exploits quasi-identifiers in the DNA data or metadata to uncover the identity of an unknown genetic dataset.\nC_LIO_LIAttribute disclosure techniques work on known DNA datasets. They use the DNA information to link the identity of a person with a sensitive phenotype.\nC_LIO_LICompletion techniques also work on known DNA data. They try to uncover sensitive genomic areas that were masked to protect the participant.\nC_LIO_LIIn the last few years, we have witnessed a rapid growth in the range of techniques and tools to conduct these privacy-breaching attacks. Currently, most of the techniques are beyond the reach of the general public, but can be executed by trained persons with varying degrees of effort.\nC_LIO_LIThere is considerable debate regarding risk management. One camp supports a pragmatic, ad-hoc approach of privacy by obscurity and the other supports a systematic, mathematically-backed approach of privacy by design.\nC_LIO_LIPrivacy by design algorithms include access control, differential privacy, and cryptographic techniques. So far, data custodians of genetic databases mainly adopted access control as a mitigation strategy.\nC_LIO_LINew developments in cryptographic techniques may usher in an additional arsenal of security by design techniques.\nC_LI

Genomics