Invention Grant
- Patent Title: Privacy-preserving genomic prediction
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Application No.: US15179777Application Date: 2016-06-10
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Publication No.: US10296709B2Publication Date: 2019-05-21
- Inventor: Kim Laine , Nicolo Fusi , Ran Gilad-Bachrach , Kristin E. Lauter
- Applicant: Microsoft Technology Licensing, LLC
- Applicant Address: US WA Redmond
- Assignee: MICROSOFT TECHNOLOGY LICENSING, LLC
- Current Assignee: MICROSOFT TECHNOLOGY LICENSING, LLC
- Current Assignee Address: US WA Redmond
- Agency: Merchant & Gould
- Main IPC: G06F17/50
- IPC: G06F17/50 ; G06F19/12 ; G06F19/18 ; G06F19/24 ; G06F21/62 ; H04L9/00

Abstract:
The techniques and/or systems described herein are directed to improvements in genomic prediction using homomorphic encryption. For example, a genomic model can be generated by a prediction service provider to predict a risk of a disease or a presence of genetic traits. Genomic data corresponding to a genetic profile of an individual can be batch encoded into a plurality of polynomials, homomorphically encrypted, and provided to a service provider for evaluation. The genomic model can be batch encoded as well, and the genetic prediction may be determined by evaluating a dot product of the genomic model data the genomic data. A genomic prediction result value can be provided to a computing device associated with a user for subsequent decrypting and decoding. Homomorphic encoding and encryption can be used such that the genomic data may be applied to the prediction model and a result can be obtained without revealing any information about the model, the genomic data, or any genomic prediction.
Public/Granted literature
- US20170357749A1 Privacy-Preserving Genomic Prediction Public/Granted day:2017-12-14
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