Dynamic attribute-based privacy-preserving genomic susceptibility testing

Abstract

Developments in the field of genomic studies have resulted in the current high availability of genomic data which, in turn, raises significant privacy concerns. As DNA information is unique and correlated among family members, it cannot be regarded just as a matter of individual privacy concern. Due to the need for privacy-enhancing methods to protect these sensitive pieces of information, cryptographic solutions are deployed and enabled scientists to work on encrypted genomic data. In this paper, we develop an attribute-based privacy-preserving susceptibility testing method in which genomic data of patients is outsourced to an untrustworthy platform. We determine the challenges for the computations required to process the outsourced data and access control simultaneously within patient-doctor interactions. We obtain a non-interactive scheme regarding the contribution of the patient which improves the safety of the user data. Moreover, we exceed the computation performance of the susceptibility testing over the encrypted genomic data while we manage attributes and embedded access policies. Also, we guarantee to protect the privacy of individuals in our proposed scheme.