Artificial Intelligence (AI) incorporating genetic and medical information have been applied in disease risk prediction, unveiling disease mechanism, and advancing therapeutics. However, AI training relies on highly sensitive and private data which significantly limit their applications and robustness evaluation. Moreover, the data access management after sharing across organization heavily relies on legal restriction, and there is no guarantee in preventing data leaking after sharing. Here, we present Genie, a secure AI platform which allows AI models to be trained on medical data securely. The platform combines the security of Intel Software Guarded eXtensions (SGX), transparency of blockchain technology, and verifiability of open algorithms and source codes. Genie shares insights of genetic and medical data without exposing anyone's raw data. All data is instantly encrypted upon upload and contributed to the models that the user chooses. The usage of the model and the value generated from the genetic and health data will be tracked via a blockchain, giving the data transparent and immutable ownership.
@article{arxiv.1811.01431,
title = {Genie: A Secure, Transparent Sharing and Services Platform for Genetic and Health Data},
author = {Shifa Zhang and Anne Kim and Dianbo Liu and Sandeep C. Nuckchady and Lauren Huang and Aditya Masurkar and Jingwei Zhang and Lawrence Tseng and Pratheek Karnati and Laura Martinez and Thomas Hardjono and Manolis Kellis and Zhizhuo Zhang},
journal= {arXiv preprint arXiv:1811.01431},
year = {2020}
}