A Study Of Genomic Privacy Protection Technology

With the rapid development of next-generation sequencing technology, the prices of DNA sequencing drop rapid, people get personal genomic data more and more easily, which will greatly facilitate the use of personal genomic data. Genomic data are very widely applied in many fields, such as medical, research, life sciences, social networks, etc., which bring many benefits to people’s lives and provide important protection for human life and scientific progress.However, personal genome data contains important sensitive information to their personal and family-related, such as genetic information, disease information, information about parent-child relationship. With the use of personal genomic data more widely, including personal medical, life science research, human genome-wide association studies, and now there is a trend towards social networking applications. Misuse and incorrect storage of personal genomic data will cause serious genomic privacy issues.In view of the existing privacy protection technologies such as anonymous, anti-status tracking, secure multiparty computation, etc. cannot fully meet user’s requirements for the protection of the genomic privacy. In many genomic data application scenarios, user’s genomic privacy cannot be guaranteed, so we need to leverage existing technology or construct a new privacy protection technologies to design privacy-preserving scheme applied to scenarios of processing genomic data. This article focuses on the application of genetic disease susceptibility testing.In view of personal genomic data privacy issues exist in the applications process. First, we propose a genome sequencing, storage, using framework for genomic data; Then, we analysis this particular application privacy issues of the genetic disease susceptibility test; Dynamic symmetry searchable encryption, symmetric encryption, pseudonyms and other privacy protection technology are used to design privacy protection scheme for such scenarios; Finally, through security analysis and performance analysis of simulation experiments, we show that the proposed scheme not only protect user’s privacy and very efficient and safe.In order to test the practical feasibility of the proposed scheme, in view of the complexity of the proposed framework and the limited our computing resources, this article only complement at the end of the phone, we develop Android application programming to complete genetic disease susceptibility test on the smartphone; By observing the experimental data, we find that the proposed scheme is entirely feasible. In comparison with the existing privacy protection scheme, we show our scheme is more efficient and more able to protect the user’s genomic privacy.