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, 2019)
2.    Solution due (Aug. 16, 2019)
3.    Winner announcement (Oct. 1)
4.    Workshop day (Oct. 26, 2019)
5.    Publication submission deadline (Nov. 30, 2019)
6.    Publication notification (TBD)


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.


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)


Winning results will be published a special issue of a journal.


Track 1 (UCSD): 
Tsung-Ting Kuo (tskuo@ucsd.edu), 
Lucila Ohno-Machado (lohnomachado@ucsd.edu)

Track 2 (UT Health): 
Arif Harmanci (Arif.O.Harmanci@uth.tmc.edu),
Miran Kim (Miran.Kim@uth.tmc.edu),
Xiaoqiang Jiang (Xiaoqian.Jiang@uth.tmc.edu)

Track 3 (IU): Haixu Tang (hatang@indiana.edu
XiaoFeng Wang (xw7@indiana.edu) 

Track 4 (IU): 
Haixu Tang (hatang@indiana.edu
XiaoFeng Wang (xw7@indiana.edu)