Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE credits
Since 2007, the cost of sequencing a whole human genome has decreased by roughly half every 4 months. As of 2014, whole genome sequencing would cost only 1,000 dollars, and, as such, Next-Generation sequencing (NGS) machines are now a source of Big Data - the Illumina HiSeq X Ten can produce up to 20 PB of data per year. The dominant open-source platform for storing and processing Big Data is Apache Hadoop. However, Hadoop does not support user identity natively, and, as genomic data is sensitive data, there are no existing solutions for multi-tenancy that meet the needs of organizations to securely store and process genomic data.
In this thesis, we address the problem for how to enable Biobank users to securely store, access, and share genomic data in Hadoop. The proposed solution of the work is based on leveraging security support in the J2EE framework, and by constraining access to Hadoop through a web application built in this project. However, HTTP(S) limits the size of files that can be transferred into web applications, and we address the follow-on problem of how to enable users to efficiently, easily, and securely copy genomic data into Hadoop. Our prototype demonstrates how Hadoop can be secured to support sensitive data, and how Big Data can be securely transported over HTTP.
2014. , 50 p.