Gene data desensitization method for realizing efficient similarity query and access control

A genetic data and access control technology, applied in the field of information security, can solve the problems of reducing data availability, focusing only, different access rights of genetic data, etc., to achieve the effect of reducing the number of elements, flexible authorization methods, and improving query and retrieval efficiency

Active Publication Date: 2019-09-20
UNIV OF ELECTRONICS SCI & TECH OF CHINA +1
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  • Abstract
  • Description
  • Claims
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AI Technical Summary

Problems solved by technology

However, by directly outsourcing genetic data to cloud servers in clear text, cloud service providers can easily obtain user sensitive information such as gene sequences, health status, etc., which poses a great risk of leakage of user privacy data.
[0003] To solve the above problems, a simple way is to use traditional encryption methods (such as AES) to encrypt the entire genetic data before outsourcing the genetic data to the cloud server; however, this will significantly reduce the availability of data, because the cloud server cannot Perform genetic similarity query in ciphertext state; therefore, it is urgent to design a safe, efficient and fully functional genetic data desensitiza

Method used

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  • Gene data desensitization method for realizing efficient similarity query and access control
  • Gene data desensitization method for realizing efficient similarity query and access control
  • Gene data desensitization method for realizing efficient similarity query and access control

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Embodiment Construction

[0062] The present invention will be described in further detail below in conjunction with the accompanying drawings and embodiments.

[0063] This embodiment proposes a genetic data desensitization method that realizes efficient ciphertext similarity query and secure access control in a cloud environment. The process is as follows figure 1 As shown, it specifically includes the following steps:

[0064] Step 1. System initialization: the system generates a public gene sequence, the data owner generates a set of role permissions for users to access data, and generates the keys required for specific hash function encryption, set pseudo-random permutation, and matrix security inner product operations;

[0065] System initialization, specifically includes the following steps:

[0066] Step 1.1 The system releases the public gene sequence ref that does not contain any sensitive information, and ref is the target sequence required for processing by the edit distance algorithm;

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Abstract

The invention belongs to the technical field of information security. The invention particularly provides a gene data desensitization method for realizing efficient similarity query and access control. The similarity query of large-scale gene data in a ciphertext environment is effectively supported; meanwhile, complex logic query is supported to meet the personalized query requirement of the user; according to the method, the authorization mode is flexible, different access authorities can be given to different data, reliable control over the data access authority of a user is achieved in the query process, in addition, a specific Hash function is adopted for compressing the data, the number of matched elements in the ciphertext state is remarkably reduced, and the query retrieval efficiency is further improved.

Description

technical field [0001] The invention belongs to the technical field of information security, and in particular relates to a genetic data desensitization method for realizing efficient similarity query and access control. Background technique [0002] Gene similarity query has become a hot research field with good prospects for medical and health applications. For example, disease prediction, through early preventive treatment to reduce the incidence of people with similar genes to the disease. With the advent of the big data era, the huge amount of genetic data and the computational overhead of similarity queries between genes have led more and more companies and enterprises to outsource local genetic data to third-party cloud servers, such as DNAnexus, Google Genomics, etc. . However, by directly outsourcing genetic data to cloud servers in clear text, cloud service providers can easily obtain user sensitive information such as gene sequences and health status, which pose...

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Application Information

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IPC IPC(8): G06F21/62G06F21/30G06F16/9532G06F16/9535H04L9/06H04L9/08H04L29/06H04L29/08
CPCG06F16/9532G06F16/9535G06F21/30G06F21/6245H04L9/0643H04L9/0861H04L9/0869H04L63/0435H04L67/10
Inventor 李洪伟刘森徐国文龚丽任彦之杨浩淼赵芸伟舒敏韩晗王文磊
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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