GenoPri'16: international workshop on genome privacy and security

GenoPri’16: International Workshop on

Genome Privacy and Security

Erman Ayday , Xiaoqian Jiang , and Bradley Malin

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VERthe past several decades, genome sequencing tech-nologies have evolved from slow and expensive sys-tems that were limited in access to a select few scientists and forensics investigators to high-throughput, relatively low-cost tools that are available to consumers. A direct con-sequence of such rapid technical progress is that genomics is becoming one of the next major challenges for privacy and security [1] because (i) a volunteer, accepting to have his genomic code made public, can leak substantial informa-tion about their ethnic heritage, as well as the genomic data of their relatives [2], [3], (ii) genetically-influenced diseases can be unveiled [4], (iii) the propensity to develop specific diseases (such as Alzheimer’s) can be revealed [5], and (iv) complex privacy issues can arise if DNA analysis is used for criminal investigations and insurance purposes [6]. As genomics is increasingly integrated into healthcare [7] and direct-to-consumer recreational services [8] (e.g., ances-try testing), the risk of genomic data leakage has grown for both individuals and their relatives. Failure to adequately protect such information could lead to societal and regula-tory backlashes, which could impede genomic research and society more generally. At the same time, there are ques-tions about the magnitude of such risks. This prompts the need for research and innovation in all aspects of genome privacy and security.

To foster research in understanding and addressing pri-vacy and security issues in genomics, we organized the 3rd International Workshop on Genome Privacy and Security (GenoPri) in 2016. This workshop aimed to bring together a highly interdisciplinary community involved in all aspects of genome privacy and security research. This workshop built on its two predecessors, GenoPri’14, and GenoPri’15, which were collocated with the Privacy Enhancing Technol-ogies Symposium (PETS) and IEEE Symposium on Security and Privacy, respectively.

GenoPri’16 aimed to expand its reach to the medical community. To accomplish this goal, GenoPri’16 was collo-cated with the American Medical Informatics Association

Annual Fall Symposium (AMIA), a premier medical infor-matics venue. The number of participants during the day exceeded 60 and the workshop included technical sessions (featuring peer-reviewed papers), two panels, a tutorial, and two invited talks. The themes of the technical sessions were (i) privacy-preserving personalized medicine, (ii) pri-vacy-preserving research, and (iii) risks and quantification of privacy. The panels focused on 1) future research direc-tions in genomics privacy and security and 2) existing and future ethical principles, policies, and legislation. The two invited talks were delivered by Dr. Shawn Murphy of the Harvard Medical School, who discussed the balance between genomic data privacy and utility in the context of clinical research informatics systems and Dr. Christian Lovis of the University Hospitals of Geneva, who discussed truth in the era of big data, genomics, and the practice of medicine.

The three papers selected to appear in this special section of the IEEE/ACM Transactions on Computational Biology and Bioinformatics were drawn from the set of accepted peer-reviewed technical papers. The papers that were accepted cover prominent perspectives of genomic privacy, including privacy measurement, exploratory research respecting pri-vacy and security, and secure genomic analytics. We have ordered the papers to illustrate the progression of privacy and security with respect to genomic data.

The first paper in this special section focuses on the issue of privacy from the perspective of inference from genomic records. Specifically, this paper from Saarland University (Germany), focuses on genomic privacy in the context of populations over time. The authors introduce a simulation-based approach for quantifying the impact of continuously sequencing and publicizing personal genomic data on a population’s genomic privacy. They account for the influ-ence of geopolitical events, such as migration, as well as sociological trends, such as interracial mating. The authors notably report that that an increasing sharing rate of geno-mic data in the future entails a substantial negative effect on the privacy of all older generations.

While the first paper sets the stage for how information can be gleaned from genomic records, the second paper considers how to compute over such data without disclos-ing the exact contents of any particular record. Specifically, this paper “Protecting Privacy and Security of Genomic Data in i2b2 with Homomorphic Encryption and Differen-tial Privacy” by Jean Louis Raisaro, Gwangbae Choi, Syl-vain Pradervand, Raphael Colsenet, Nathalie Jacquemont, Nicolas Rosat, Vincent Mooser, and Jean-Pierre Hubaux from Ecole Polytechnique Federale de Lausanne (EPFL) and

 E. Ayday is with the Department of Computer Engineering, Bilkent Uni-versity, Ankara, Turkey. E-mail: erman@cs.bilkent.edu.tr.

 X. Jiang is with the School of Biomedical Informatics, University of Texas Health Science Center at Houston, 7000 Fannin Street, Houston, TX 77030. E-mail: Xiaoqian.Jiang@uth.tmc.edu.

 B. Malin is with the School of Medicine, Vanderbilt University, Nashville, TN 37235. E-mail: b.malin@vanderbilt.edu.

For information on obtaining reprints of this article, please send e-mail to: reprints@ieee.org, and reference the Digital Object Identifier below.

Digital Object Identifier no. 10.1109/TCBB.2018.2856959

IEEE/ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS, VOL. 15, NO. 5, SEPTEMBER/OCTOBER 2018 1403

1545-5963ß 2018 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See ht_tp://www.ieee.org/publications_standards/publications/rights/index.html for more information.

Lausanne University Hospital (Switzerland) and focuses on privacy-preserving cohort discovery and exploration. In this problem, the goal is to enable biomedical scientists to use data derived from electronic medical records, to detect groups of patients who meet specific inclusion and exclu-sion criteria. The authors report on the design of an efficient privacy-preserving explorer for genetic cohorts, as well as the deployment and evaluation of the system in a real oper-ational setting. The solution is built on top of the popular i2b2 (Informatics for Integrating Biology and the Bedside) software suite relies upon homomorphic encryption for secure data processing. The authors illustrate how their sys-tem supports exploration of 3,000 genetic variants over a cohort of 5,000 individuals in less than 5 seconds using com-modity hardware.

The last paper in this section moves beyond exploratory data investigations to consider how to prevent privacy leaks in the context of statistical computing. This paper from a team at the company Cybernetica AS (Estonia) specifically considers privacy leaks that can transpire in the context of computation for population stratification. In this work, the authors utilize matrix decomposition, in the form of principal components analysis, to reduce the dimensionality of a privacy-preserving setting through cryptographically secure multi-party computation. This is an important adv-ancement because this type of matrix analysis is common in genome-based computations, such as modeling ancestral heritage in populations. In doing so, present a software implementation, as well as experimental results showing the performance of the approach.

We are highly encouraged by the increased participation and witnessed the growing of an interdisciplinary research community. The joint meeting with AMIA has been fruitful and many participants benefited from the cross-fertilization from each other. We are planning to continue the momen-tum in 2017 to work closely with the biomedical informatics community and push the fronts of genomic privacy technol-ogy to address the real world challenges. Thus, GenoPri’17 will be collocated with GA4GH Security Working Group (SWG) and American Society of Human Genetics (ASHG) Annual Meeting.

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CKNOWLEDGMENTS

The authors are listed in alphabetical order.

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EFERENCES

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[2] S. S. Shringarpure and C. D. Bustamante, “Privacy leaks from genomic data-sharing beacons,” Amer. J. Hum. Genetics, vol. 97, pp. 631–646, 2015.

[3] N. Homer, S. Szelinger, M. Redman, D. Duggan, W. Tembe, J. Muehling, et al., “Resolving individuals contributing trace amounts of DNA to highly complex mixtures using high-density SNP genotyping microarrays,” PLoS Genet, vol. 4, no. 8, 2008, Art. no. e1000167.

[4] A. Apoc, “On Jim Watson’s APOE status: Genetic information is hard to hide,” Eur. J. Hum. Genetics Citeseer, vol. 17, pp. 147–149, 2009. [5] R. Wang, Y. F. Li, X. Wang, H. Tang, and X. Zhou, “Learning your identity and disease from research papers: information leaks in genome wide association study,” Proc. 16th ACM Conf. Comput. Commun. Security, 2009, Art. no. 534-544.

[6] M. A. Jobling and P. Gill, “Encoded evidence: DNA in forensic ana-lysis,” Nature Rev. Genetics, vol. 5, no. 10, pp. 739–751, Oct. 2004. PMID: 15510165

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[8] J. S. Roberts and J. Ostergren, “Direct-to-consumer genetic testing and personal genomics: A review of recent empirical evidence,” Current Genetic Med. Reports, vol. 1, no. 3, pp. 182–200, 2013. Erman Ayday received the MS and PhD degrees from the School of Electrical and Computer Engineering (ECE), Georgia Institute of Tech-nology, Atlanta, GA, in 2007 and 2011, respectively, under the supervi-sion of Dr. Faramarz Fekri. He is an assistant professor of computer science with Bilkent University, Ankara, Turkey. Before that, he was a post-doctoral researcher with EPFL, Switzerland, working with Prof. Jean-Pierre Hubaux. His research interests include privacy-enhancing technologies (including big data and genomic privacy), applied cryptog-raphy and data security, trust and reputation management, and infer-ence from big data. He is the recipient of the Distinguished Student Paper Award at IEEE S&P 2015, the 2010 Outstanding Research Award from CSIP at Georgia Tech, and the 2011 ECE Graduate Research Assistant Excellence Award from Georgia Tech. His other various accomplishments include several patents, research grants, and a H2020 Marie Curie individual fellowship. He has published more than 50 peer-reviewed papers in prestigious venues including ACM CCS, IEEE S&P, and the IEEE Transactions on Dependable and Secure Computing. He has been also serving on the program committee of many conferences including ACM CCS, NDSS, and AsiaCCS. Xiaoqian Jiang received the PhD degree in computer science from Carnegie Mellon University. He is currently an associate professor in the School of Biomedical Informatics with the University of Texas Health Science Center at Houston. He is an associate editor of BMC Medical Informatics and Decision Making and serves as an editorial board mem-ber of the Journal of American Medical Informatics Association. He works primarily in health data privacy and predictive models in biomedi-cine. He is a recipient of Distinguished Paper Award from the American Medical Informatics Association Clinical Research Informatics (CRI) Summit in 2012 and 2013, respectively. He organized iDASH genomic privacy workshops and served as a reviewer for major biomedical infor-matics venues like the Journal of the American Medical Inforinfor-matics Association, the Journal of Biomedical Informatics, the IEEE/ACM Transactions on Computational Biology and Bioinformatics and confer-ences like AMIA and TBC.

Bradley Malin received the BS degree in biological sciences, the MS degree in machine learning, the MPhil degree in public policy and man-agement, and the PhD degree in computer science, all from Carnegie Mellon University, Pittsburgh, PA, USA. He is currently a professor of the biomedical informatics, biostatistics, and computer science at Van-derbilt University, Nashville, TN, USA, where he directs the NIH Center of Excellence in Ethical, Legal, and Social Implications Research that focuses on genomics and privacy. His current research interests include big data mining, biomedical informatics, and genomic data privacy. His research has been supported by the Patient Centered Outcomes Research Institute, National Science Foundation, and the National Insti-tutes of Health, for which he has directed a data privacy and research consultation team for the Electronic Medical Records and Genomics (eMERGE) consortium since 2007 and serves as co-chair of the Privacy and Security Working Group of the Precision Medicine Initiative. His research has been cited in various governmental proceedings on health information privacy and security. He is a recipient of the Presidential Early Career Award for Scientists and Engineers from the White House. He is a member of the IEEE.

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