Pathogenic gene detection method based on privacy protection intersection calculation protocol

Abstract

The invention discloses a pathogenic gene detection method based on a privacy protection intersection calculation protocol. According to the method, elements which do not exist in an intersection of aset held by a server and a set held by a client are filtered out by adopting a Bloom filter; the elements of the server are mapped to hash buckets through simple hash mapping, and the elements of theclient are mapped to a two-dimensional hash table through cuckoo hash mapping; a one-out-of-N ROT extension protocol is executed on the elements in each bucket; an encryption sequence generated by the server is sent to the client; intersection calculation is carried out on the output of the client and the encryption sequence of the server; the set of the client, which has been subjected to filtering and hash mapping, is compared with a calculation result; and the intersection elements of the two parties are finally obtained, the information of any party except the intersection will not leak.With the method of the invention adopted, the safety of gene detection can be ensured, and running time and communication overhead are reduced.

Description

Technical field [0001] The invention relates to the technical field of secure multi-party computing, in particular to a method for detecting pathogenic genes based on a privacy protection intersection computing protocol. Background technique [0002] With the advancement of modern medicine, human whole-genome sequencing technology has become more and more efficient, accurate, and low-cost, making it easier to obtain personal genome data. Because it contains important and sensitive personal information, such as heredity, disease, relatives, identity, etc., genomic data is widely used as a series of biological tests, such as genetic compatibility testing, personalized medicine, disease detection, and paternity testing. In addition, at this stage, the environment for the use of genetic data is not perfect, and the gene sequencing market is chaotic, making the privacy and security of the genetic data sharing process huge hidden dangers. [0003] In the existing gene sequencing researc...

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Problems solved by technology

Shen et al [L.Shen, R.Baronio, X.Chen, and D.Wang, “Efficient and Private Set Intersection of Human Genomes,” in 2018 IEEE International Conference on Bioinformatics and Biomedicine, 2018 BIBM, pp.761-764.] A PSI scheme based on a trade-off hash and an N-selected Random Oblivious Transfer (ROT) extension protocol is proposed for genetic testing

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