A security framework for population-scale genomics analysis - Gholami, Ali; Dowling, Jim; Laure, Erwin (2015 International Conference on High Performance Computing and Simulation (HPCS), 2015)
Biobanks store genomic material from identifiable individuals. Recently many population-based studies have started sequencing genomic data from biobank samples and cross-linking the genomic data with clinical data, with the goal of discovering new insights into disease and clinical treatments. However, the use of genomic data for research has far-reaching implications for privacy and the relations between individuals and society. In some jurisdictions, primarily in Europe, new laws are being or have been introduced to legislate for the protection of sensitive data relating to individuals, and biobank-specific laws have even been designed to legislate for the handling of genomic data and the clear definition of roles and responsibilities for the owners and processors of genomic data. This paper considers the security questions raised by these developments. We introduce a new threat model that enables the design of cloud-based systems for handling genomic data according to privacy legislation. We also describe the design and implementation of a security framework using our threat model for BiobankCloud, a platform that supports the secure storage and processing of genomic data in cloud computing environments.