PRINCESS: Privacy-protecting Rare disease International Network Collaboration via Encryption through Software guard extensionS | Zendy

Feng Chen | Zendy; Shuang Wang | Zendy; Xiaoqian Jiang | Zendy; Sijie Ding | Zendy; Yao Lu | Zendy; Jihoon Kim | Zendy; S. Cenk Ṣahinalp | Zendy; Chisato Shimizu | Zendy; Jane C. Burns | Zendy; Victoria Wright | Zendy; Eileen Png | Zendy; Martin L. Hibberd | Zendy; David Lloyd | Zendy; Hai Yang | Zendy; Amalio Telenti | Zendy; Cinnamon S. Bloss | Zendy; Dov Fox | Zendy; Kristin Lauter | Zendy; Lucila OhnoMachado | Zendy

Open Access

PRINCESS: Privacy-protecting Rare disease International Network Collaboration via Encryption through Software guard extensionS

Author(s) -

Feng Chen,

Shuang Wang,

Xiaoqian Jiang,

Sijie Ding,

Yao Lu,

Jihoon Kim,

S. Cenk Ṣahinalp,

Chisato Shimizu,

Jane C. Burns,

Victoria Wright,

Eileen Png,

Martin L. Hibberd,

David Lloyd,

Hai Yang,

Amalio Telenti,

Cinnamon S. Bloss,

Dov Fox,

Kristin Lauter,

Lucila OhnoMachado

Publication year - 2016

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btw758

Subject(s) - homomorphic encryption , computer science , encryption , guard (computer science) , software , computer security , computation , secure multi party computation , cryptography , operating system , algorithm , programming language

We introduce PRINCESS, a privacy-preserving international collaboration framework for analyzing rare disease genetic data that are distributed across different continents. PRINCESS leverages Software Guard Extensions (SGX) and hardware for trustworthy computation. Unlike a traditional international collaboration model, where individual-level patient DNA are physically centralized at a single site, PRINCESS performs a secure and distributed computation over encrypted data, fulfilling institutional policies and regulations for protected health information.

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