Probability distribution estimation method of multi-dimensional group intelligence perception data with local privacy protection

A technology of group intelligence sensing data and privacy protection, applied in the field of privacy protection, to achieve the effect of reducing time complexity and space complexity, reducing space size, and reducing time and space complexity

Inactive Publication Date: 2019-03-29
XI AN JIAOTONG UNIV
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Problems solved by technology

[0003] The purpose of the present invention is to overcome the shortcomings of the above-mentioned prior art and provide a method for estimating the probability distribution of multi-dimen

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  • Probability distribution estimation method of multi-dimensional group intelligence perception data with local privacy protection
  • Probability distribution estimation method of multi-dimensional group intelligence perception data with local privacy protection
  • Probability distribution estimation method of multi-dimensional group intelligence perception data with local privacy protection

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Embodiment Construction

[0041] The present invention will be described in further detail below in conjunction with the accompanying drawings.

[0042] refer to figure 1 The method for estimating the probability distribution of high-dimensional crowd sensing data with local privacy protection provided by the present invention comprises the following steps:

[0043] 1) Local data processing: For the i-th user, suppose there is an original data record with d attributes For each attribute A j (j=1,2,...,d), first use the hash function H j Map raw data to length m j The Bloom filter string

[0044]

[0045] then in each bit in Will be randomly assigned according to the following formula

[0046]

[0047] where f∈(0,1) is a user-controlled random flip probability that can be used to specify the degree of randomness in local privacy protection, and also potentially determines the degree of privacy protection,

[0048] Finally, the bit strings on each attribute are concatenated to obtain a r...

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Abstract

The invention discloses a probability distribution estimation method of multi-dimensional group intelligence perception data with local privacy protection, which solves the utility and efficiency problems of multi-dimensional data in distribution estimation. Each user firstly perturbs the data at the local end and then sends the perturbed data to the central server, When the central server receives the data sent by all users, Lasso regression is used to multidimensional data with local privacy protection to eliminate redundant candidate states, And the fastest initial value of the solution based on Lasso regression is substituted into the expectation maximization algorithm, and then the convergence of the expectation maximization algorithm is applied to iterate the initial value to obtainthe accurate probability distribution estimate quickly.

Description

technical field [0001] The invention belongs to the field of privacy protection, and in particular relates to a method for estimating the probability distribution of multi-dimensional crowd sensing data with local privacy protection. Background technique [0002] Nowadays, with the rise of different integrated IoT sensor technologies and crowd-sensing systems, information of various attribute dimensions can be collected by crowdsourcing. And these dimensional information containing multiple different attributes can also be analyzed and mined to generate more useful knowledge, which is finally fed back to the participants of the system. However, due to the aggregation and release of crowd sensing data, the privacy of participants is easily speculated and identified. Especially for high-dimensional data, the correlation between its attributes will make the existing privacy protection technology invalid. Generally speaking, its privacy threats are reflected in two aspects: 1)...

Claims

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Application Information

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IPC IPC(8): G06N7/00G06F21/62
CPCG06F21/6245G06N7/01
Inventor 杨新宇任雪斌翟守沛姚向华王腾魏洁王舒阳
Owner XI AN JIAOTONG UNIV
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