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<p class="MsoNormal" align="center" style="text-align:center"><span style="font-family:"Arial",sans-serif;color:black">2019 NIH iDASH Secure Genome Analysis Competition and Workshop<o:p></o:p></span></p>
<p class="MsoNormal" align="center" style="text-align:center"><span style="font-family:"Arial",sans-serif;color:black">(October 26, 2019, Indianapolis, Indiana, USA)<o:p></o:p></span></p>
<p class="MsoNormal" align="center" style="text-align:center"><span style="font-family:"Arial",sans-serif;color:black"><o:p> </o:p></span></p>
<p class="MsoNormal" align="center" style="text-align:center"><span style="font-family:"Arial",sans-serif;color:black">Call for Participation<o:p></o:p></span></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p style="margin:0in;margin-bottom:.0001pt;text-align:justify;text-justify:inter-ideograph">
<span style="font-size:11.0pt;font-family:"Arial",sans-serif;color:black">The 6th iDASH Secure Genome Analysis Competition and Workshop is calling for participation from the academia and the industry to showcase state-of-the-art privacy technologies for protecting
real-world biomedical data analysis. In the past 5 years, the iDASH competition has been serving as a bridge between the privacy/security research and the biomedical research, challenging the security community to come up with the best solutions that can
offer practical supports for privacy-preserving biomedical computing. It has been widely considered to be a benchmark for evaluating data privacy technologies, particularly when they are applied to biomedical data analysis, and a key source for the biomedical
and genomics researchers to seek usable solutions for protecting their data and computing tasks. This year’s competition is characterized by 4 tracks as described below.</span><o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p style="margin:0in;margin-bottom:.0001pt"><b><span style="font-size:11.0pt;font-family:"Arial",sans-serif;color:black">Competition Tasks</span></b><o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p style="margin:0in;margin-bottom:.0001pt"><u><span style="font-size:11.0pt;font-family:"Arial",sans-serif;color:black;background:white">Track 1: Distributed Gene-Drug Interaction Data Sharing based on Blockchain and Smart Contracts</span></u><span style="font-size:11.0pt;font-family:"Arial",sans-serif;color:black;background:white">
</span><o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p style="margin:0in;margin-bottom:.0001pt"><span style="font-size:11.0pt;font-family:"Arial",sans-serif;color:black">The competitors are asked to develop smart contracts on a blockchain network to share gene-drug interaction data in a distributed way.</span><o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p style="margin:0in;margin-bottom:.0001pt"><u><span style="font-size:11.0pt;font-family:"Arial",sans-serif;color:black;background:white">Track 2: Secure Genotype Imputation using Homomorphic Encryption</span></u><span style="font-size:11.0pt;font-family:"Arial",sans-serif;color:black;background:white">
</span><o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p style="margin:0in;margin-bottom:.0001pt"><span style="font-size:11.0pt;font-family:"Arial",sans-serif;color:black;background:white">The competitors are required to</span><span style="font-size:11.0pt;font-family:"Arial",sans-serif;color:black"> develop a
homomorphic encryption (HE) based method for performing genotype imputation</span><o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p style="margin:0in;margin-bottom:.0001pt"><u><span style="font-size:11.0pt;font-family:"Arial",sans-serif;color:black;background:white">Track 3: Outsourcing Privacy-preserving Machine Learning as a Service through TEE</span></u><span style="font-size:11.0pt;font-family:"Arial",sans-serif;color:black;background:white">
</span><o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p style="margin:0in;margin-bottom:.0001pt"><span style="font-size:11.0pt;font-family:"Arial",sans-serif;color:black;background:white">The competitors are expected to implement a trained deep learning model for disease prediction under the protection of SGX,
Intel’s trusted execution environment, so the model can work on encrypted genomic data uploaded by the user.
</span><o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p style="margin:0in;margin-bottom:.0001pt"><u><span style="font-size:11.0pt;font-family:"Arial",sans-serif;color:black;background:white">Track 4: Privacy-preserving machine learning
</span></u><o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p style="margin:0in;margin-bottom:.0001pt"><span style="font-size:11.0pt;font-family:"Arial",sans-serif;color:black">The competitors are tasked to train a machine learning model on gene expression data for breast tumors, with all the data secretly shared across
multiple servers. </span><o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p style="margin:0in;margin-bottom:.0001pt"><b><span style="font-size:11.0pt;font-family:"Arial",sans-serif;color:black">Time line</span></b><o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p style="mso-margin-top-alt:0in;margin-right:0in;margin-bottom:0in;margin-left:.5in;margin-bottom:.0001pt;text-indent:-.25in;mso-list:l0 level1 lfo2;vertical-align:baseline">
<![if !supportLists]><span style="font-size:11.0pt;font-family:"Arial",sans-serif;color:black"><span style="mso-list:Ignore">1.<span style="font:7.0pt "Times New Roman"">
</span></span></span><![endif]><span style="font-size:11.0pt;font-family:"Arial",sans-serif;color:black">Competition start (May 13)<o:p></o:p></span></p>
<p style="mso-margin-top-alt:0in;margin-right:0in;margin-bottom:0in;margin-left:.5in;margin-bottom:.0001pt;text-indent:-.25in;mso-list:l0 level1 lfo2;vertical-align:baseline">
<![if !supportLists]><span style="font-size:11.0pt;font-family:"Arial",sans-serif;color:black"><span style="mso-list:Ignore">2.<span style="font:7.0pt "Times New Roman"">
</span></span></span><![endif]><span style="font-size:11.0pt;font-family:"Arial",sans-serif;color:black">Solution due (Aug. 16)<o:p></o:p></span></p>
<p style="mso-margin-top-alt:0in;margin-right:0in;margin-bottom:0in;margin-left:.5in;margin-bottom:.0001pt;text-indent:-.25in;mso-list:l0 level1 lfo2;vertical-align:baseline">
<![if !supportLists]><span style="font-size:11.0pt;font-family:"Arial",sans-serif;color:black"><span style="mso-list:Ignore">3.<span style="font:7.0pt "Times New Roman"">
</span></span></span><![endif]><span style="font-size:11.0pt;font-family:"Arial",sans-serif;color:black">Winner announcement (Oct. 1)<o:p></o:p></span></p>
<p style="mso-margin-top-alt:0in;margin-right:0in;margin-bottom:0in;margin-left:.5in;margin-bottom:.0001pt;text-indent:-.25in;mso-list:l0 level1 lfo2;vertical-align:baseline">
<![if !supportLists]><span style="font-size:11.0pt;font-family:"Arial",sans-serif;color:black"><span style="mso-list:Ignore">4.<span style="font:7.0pt "Times New Roman"">
</span></span></span><![endif]><span style="font-size:11.0pt;font-family:"Arial",sans-serif;color:black">Workshop day (Oct. 26)<o:p></o:p></span></p>
<p style="mso-margin-top-alt:0in;margin-right:0in;margin-bottom:0in;margin-left:.5in;margin-bottom:.0001pt;text-indent:-.25in;mso-list:l0 level1 lfo2;vertical-align:baseline">
<![if !supportLists]><span style="font-size:11.0pt;font-family:"Arial",sans-serif;color:black"><span style="mso-list:Ignore">5.<span style="font:7.0pt "Times New Roman"">
</span></span></span><![endif]><span style="font-size:11.0pt;font-family:"Arial",sans-serif;color:black">Publication submission deadline (Nov. 30)<o:p></o:p></span></p>
<p style="mso-margin-top-alt:0in;margin-right:0in;margin-bottom:0in;margin-left:.5in;margin-bottom:.0001pt;text-indent:-.25in;mso-list:l0 level1 lfo2;vertical-align:baseline">
<![if !supportLists]><span style="font-size:11.0pt;font-family:"Arial",sans-serif;color:black"><span style="mso-list:Ignore">6.<span style="font:7.0pt "Times New Roman"">
</span></span></span><![endif]><span style="font-size:11.0pt;font-family:"Arial",sans-serif;color:black">Publication notification (TBD)<o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-size:12.0pt;font-family:"Times New Roman",serif"><o:p> </o:p></span></p>
<p style="margin:0in;margin-bottom:.0001pt"><b><span style="font-size:11.0pt;font-family:"Arial",sans-serif;color:black">Evaluation</span></b><o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p style="margin:0in;margin-bottom:.0001pt;text-align:justify;text-justify:inter-ideograph">
<span style="font-size:11.0pt;font-family:"Arial",sans-serif;color:black">The outcomes of the competition will be evaluated by interdisciplinary teams at Indiana University, UC San Diego, and UT Health, based upon the performance of a solution and its privacy
guarantee. </span><o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p style="margin:0in;margin-bottom:.0001pt"><b><span style="font-size:11.0pt;font-family:"Arial",sans-serif;color:black">Organization</span></b><o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p style="margin:0in;margin-bottom:.0001pt"><span style="font-size:11.0pt;font-family:"Arial",sans-serif;color:black">General Chairs: Haixu Tang and XiaoFeng Wang (Indiana University)</span><o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p style="margin:0in;margin-bottom:.0001pt"><span style="font-size:11.0pt;font-family:"Arial",sans-serif;color:black">Organization Committee: XiaoFeng Wang (IU), Haixu Tang (IU), Xiaoqian Jiang (UT Health), Miran Kim (UT Health), Arif Harmanci (UT Health),
Tsung-Ting Kuo (UCSD) and Lucila Ohno-Machado (UCSD)</span><o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p style="margin:0in;margin-bottom:.0001pt"><b><span style="font-size:11.0pt;font-family:"Arial",sans-serif;color:black">Publication</span></b><o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p style="margin:0in;margin-bottom:.0001pt"><span style="font-size:11.0pt;font-family:"Arial",sans-serif;color:black">Winning results will be published a special issue of a journal.
</span><o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p style="margin:0in;margin-bottom:.0001pt"><b><span style="font-size:11.0pt;font-family:"Arial",sans-serif;color:black">Contact</span></b><o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p style="margin:0in;margin-bottom:.0001pt"><span style="font-size:11.0pt;font-family:"Arial",sans-serif;color:black">Track 1 (UCSD): Tsung-Ting Kuo (</span><a href="mailto:tskuo@ucsd.edu"><span style="font-family:"Arial",sans-serif;color:#1155CC">tskuo@ucsd.edu</span></a><span style="font-size:11.0pt;font-family:"Arial",sans-serif;color:black">),
Lucila Ohno-Machado (</span><a href="mailto:lohnomachado@ucsd.edu"><span style="font-family:"Arial",sans-serif;color:#1155CC">lohnomachado@ucsd.edu</span></a><span style="font-size:11.0pt;font-family:"Arial",sans-serif;color:black">)
</span><o:p></o:p></p>
<p style="margin:0in;margin-bottom:.0001pt"><span style="font-size:11.0pt;font-family:"Arial",sans-serif;color:black">Track 2 (UT Health): Arif Harmanci (</span><a href="mailto:Arif.O.Harmanci@uth.tmc.edu"><span style="font-family:"Arial",sans-serif;color:#1155CC">Arif.O.Harmanci@uth.tmc.edu</span></a><span style="font-size:11.0pt;font-family:"Arial",sans-serif;color:black">),
Miran Kim (</span><a href="mailto:Miran.Kim@uth.tmc.edu"><span style="font-family:"Arial",sans-serif;color:#1155CC">Miran.Kim@uth.tmc.edu</span></a><span style="font-size:11.0pt;font-family:"Arial",sans-serif;color:black">), Xiaoqiang Jiang (</span><a href="mailto:Xiaoqian.Jiang@uth.tmc.edu"><span style="font-family:"Arial",sans-serif;color:#1155CC">Xiaoqian.Jiang@uth.tmc.edu</span></a><span style="font-size:11.0pt;font-family:"Arial",sans-serif;color:black">)</span><o:p></o:p></p>
<p style="margin:0in;margin-bottom:.0001pt"><span style="font-size:11.0pt;font-family:"Arial",sans-serif;color:black">Track 3 (IU): Haixu Tang (</span><a href="mailto:hatang@indiana.edu"><span style="font-family:"Arial",sans-serif;color:#1155CC">hatang@indiana.edu</span></a><span style="font-size:11.0pt;font-family:"Arial",sans-serif;color:black">),
XiaoFeng Wang (</span><a href="mailto:xw7@indiana.edu"><span style="font-family:"Arial",sans-serif;color:#1155CC">xw7@indiana.edu</span></a><span style="font-size:11.0pt;font-family:"Arial",sans-serif;color:black">)</span><o:p></o:p></p>
<p class="MsoNormal"><span style="font-family:"Arial",sans-serif;color:black">Track 4 (IU): Haixu Tang (</span><a href="mailto:hatang@indiana.edu"><span style="font-family:"Arial",sans-serif;color:#1155CC">hatang@indiana.edu</span></a><span style="font-family:"Arial",sans-serif;color:black">),
XiaoFeng Wang (</span><a href="mailto:xw7@indiana.edu"><span style="font-family:"Arial",sans-serif;color:#1155CC">xw7@indiana.edu</span></a><span style="font-family:"Arial",sans-serif;color:black">) </span><o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal"><span style="font-family:"Arial",sans-serif;color:black">Best,<o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-family:"Arial",sans-serif;color:black"><o:p> </o:p></span></p>
<p class="MsoNormal"><span style="font-family:"Arial",sans-serif;color:black">2019 iDASH Privacy & Security Workshop organizers<o:p></o:p></span></p>
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