Multi-dimensional data local privacy protection method based on connection function in crowd sensing system
A crowd-sensing system and connection function technology, applied in the field of privacy protection, can solve the problems of dimensional disaster, vulnerability to internal attacks, reduced signal-to-noise ratio, etc., to improve utility, avoid dimensional disaster, and effectively protect privacy.
Active Publication Date: 2020-10-27
XI AN JIAOTONG UNIV
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Problems solved by technology
On the one hand, most of the existing methods assume that the server is trusted, that is, non-local privacy protection, which makes it vulnerable to internal attacks; on the other hand, the output of multi-dimensional sensing data is huge, and when the dimension of sensing data increases, the existing methods are easy to suffer from the "curse of dimensionality", and the signal-to-noise ratio will be severely reduced
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[0039] The present invention will be described in further detail below in conjunction with the accompanying drawings.
[0040] refer to figure 1 , the multi-dimensional data local privacy protection method based on connection function in the intelligent perception system provided by the present invention, specifically comprises the following steps:
[0041] Step 1 Perception data local privacy conversion: Given the d-dimensional perception data D of N users, the data of each user is directly hashed into a bit string at the user end, and then the bit string is randomly flipped to obtain a privacy-protected bit string , and sent to the server, the expression to obtain differential privacy protection is
[0042]
[0043] Among them, ε represents the degree of differential privacy protection, h is the number of hash functions, and f is the flip probability;
[0044] Step1 specifically includes the following steps:
[0045] Step1-1 hash map: d-dimensional data for each user ...
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The invention discloses a multidimensional data local privacy protection method based on a connection function in an intelligent perception system. The method of the invention is firstly based on a method of local privacy conversion, local privacy protection is carried out on the perceptual data of the participating users at the user end, and then sampling and synthesizing the privacy preserved data based on the connection function, Compared with the general privacy protection method, the invention not only can provide local differential privacy protection at the user end, but also can improvethe utility of the published data by reducing the multidimensional perceived data range space. In the process of realizing the invention, the dimensionality reduction processing of the multidimensional data is realized, and the overhead is limited to the part of local conversion and two-dimensional probability distribution estimation, without complex operation or encryption and decryption. In thegroup intelligence perception system, the invention is simple, easy to realize, strong in expansibility and high in practical value.
Description
technical field [0001] The invention belongs to the field of privacy protection, and in particular relates to a multi-dimensional data local privacy protection method based on a connection function in a crowd sensing system. Background technique [0002] With the advent and rapid development of the information age, a wide range of data sources and diverse data fusion have formed a real big data group intelligence sensing system. The sensing data from a large number of participating users will be aggregated on the server side, and finally the server will aggregate the Multi-dimensional group intelligence sensing data is sent to third-party organizations for analysis and research, so as to facilitate people's production and life and provide a more efficient social environment. However, directly publishing high-dimensional sensing data will expose the privacy information of participating users, and due to the correlation between high-dimensional crowd intelligence data attribut...
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IPC IPC(8): G06F21/62G06F21/60
CPCG06F21/602G06F21/6245
Inventor 杨新宇王腾任雪斌姚向华魏洁翟守沛王舒阳
Owner XI AN JIAOTONG UNIV