Enabling Privacy-Preserving Sharing of Genomic Data for GWASs in Decentralized Networks

ABSTRACT

The human genome can reveal sensitive information and is potentially re-identifiable, which raises privacy and security concerns about sharing such data on wide scales. In this work, we propose a preventive approach for privacy-preserving sharing of genomic data in decentralized networks for Genome-wide association studies (GWASs), which have been widely used in discovering the association between genotypes and phenotypes. The key components of this work are: a decentralized secure network, with a privacy- preserving sharing protocol, and a gene fragmentation framework that is trainable in an end-to-end manner. Our experiments on real datasets show the effectiveness of our privacy-preserving approaches as well as significant improvements in efficiency when compared with recent, related algorithms.

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Index Terms

• Security and privacy

  • Human and societal aspects of security and privacy

    • Privacy protections

    • Usability in security and privacy

  • Network security

    • Security protocols

  • Software and application security

    • Web application security

  • Systems security

    • Distributed systems security