2019 NIH iDASH Secure Genome Analysis Competition and Workshop (October 26, 2019, Indianapolis, Indiana, USA)
Call for Participation 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. Competition Tasks Track 1: Distributed Gene-Drug Interaction Data Sharing based on Blockchain and Smart Contracts The competitors are asked to develop smart contracts on a blockchain network to share gene-drug interaction data in a distributed way. Track 2: Secure Genotype Imputation using Homomorphic Encryption The competitors are required to develop a homomorphic encryption (HE) based method for performing genotype imputation Track 3: Outsourcing Privacy-preserving Machine Learning as a Service through TEE 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. Track 4: Privacy-preserving machine learning 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. Time line 1. Competition start (May 13) 2. Solution due (Aug. 16) 3. Winner announcement (Oct. 1) 4. Workshop day (Oct. 26) 5. Publication submission deadline (Nov. 30) 6. Publication notification (TBD) Evaluation 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. Organization General Chairs: Haixu Tang and XiaoFeng Wang (Indiana University) 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) Publication Winning results will be published a special issue of a journal. Contact Track 1 (UCSD): Tsung-Ting Kuo ([email protected]<mailto:[email protected]>), Lucila Ohno-Machado ([email protected]<mailto:[email protected]>) Track 2 (UT Health): Arif Harmanci ([email protected]<mailto:[email protected]>), Miran Kim ([email protected]<mailto:[email protected]>), Xiaoqiang Jiang ([email protected]<mailto:[email protected]>) Track 3 (IU): Haixu Tang ([email protected]<mailto:[email protected]>), XiaoFeng Wang ([email protected]<mailto:[email protected]>) Track 4 (IU): Haixu Tang ([email protected]<mailto:[email protected]>), XiaoFeng Wang ([email protected]<mailto:[email protected]>) Best, 2019 iDASH Privacy & Security Workshop organizers
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