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Big data desensitization method in urban planning

A technology of urban planning and big data, applied in the fields of digital data protection, data processing application, electrical digital data processing, etc., can solve the problem of no protection method, etc., and achieve the effect of protecting the privacy of needs

Active Publication Date: 2021-01-05
天津市城市规划设计研究总院有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

But currently there is no corresponding protection method

Method used

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  • Big data desensitization method in urban planning
  • Big data desensitization method in urban planning

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0034] figure 1 It is a flow chart of the method for desensitizing big data in urban planning according to the first specific embodiment of the present invention.

[0035] The desensitization method of big data in urban planning is applied to the desensitization system. The desensitization system includes a data demander, a data provider and a third-party trust platform. The third-party trust platform includes an external inaccessible encryption mode confirmation chip. The externally inaccessible encryption mode in the third-party trust platform confirms that the hash algorithm in the chip is implanted by the manufacturer when it leaves the factory, and cannot be modified later.

[0036] The method includes:

[0037] Step 1: The data demander uses the random number generator to generate the first random number t.

[0038] Step 2: The data requester generates a data request message and sends it to the third-party trusted platform. The data request message includes: the first ...

Embodiment 2

[0057] figure 2 The block diagram of the big data desensitization system in urban planning according to the second specific embodiment of the present invention.

[0058] A desensitization system for big data in urban planning. The desensitization system includes a data demander, a data provider, and a third-party trust platform. The third-party trust platform includes an externally inaccessible encryption mode confirmation chip. The externally inaccessible encryption mode in the third-party trust platform confirms that the hash algorithm in the chip is implanted by the manufacturer when it leaves the factory, and cannot be modified later.

[0059] The system includes:

[0060] Module 1: The data demander uses the random number generator to generate the first random number t.

[0061] Module 2: The data requester generates a data request message and sends it to the third-party trusted platform. The data request message includes: the first random data t, the data provider ID,...

Embodiment 3

[0080] A computer system for desensitizing big data in urban planning, including a processor, a memory, and the memory is used to perform the following steps:

[0081] Step 1: The data demander uses the random number generator to generate the first random number t.

[0082] Step 2: The data requester generates a data request message and sends it to the third-party trusted platform. The data request message includes: the first random data t, the data provider ID, and the desired data.

[0083] Step 3: After the third-party trusted platform obtains the data request message, the first random number t therein is sent to an external inaccessible encryption mode confirmation chip, which includes a hash operation logic module k=hash(t), The input is the first random number t, and the output value k is between [0, n-1]; n is the number of homomorphic encryption modes that the third-party trusted platform can provide, and is a natural number greater than 1.

[0084] Preferably, the en...

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Abstract

The invention discloses a big data desensitization method in urban planning, which is applied to a desensitization system. The desensitization system comprises a data demander, a data provider and a third-party trust platform, wherein the third-party trust platform comprises an external inaccessible encryption mode confirmation chip. A third-party trust center is added to serve as a center node toprovide support related to trust, and the structure that in the prior art, urban planning is independent communication between a data demander and a data provider is changed. Through the hash algorithm, the selection of the encryption mode is realized, only one random number needs to be transmitted, and the transmission of a specific encryption mode is avoided. By setting the mode of interferingthe data demand, the data provider cannot know the real demand of the data demander, so that the demand privacy of the data demander is protected.

Description

technical field [0001] The invention relates to the big tree data security technology in the field of urban planning. Background technique [0002] With the increasing complexity of urban planning, more and more data needs to be considered, especially since the large-scale use of big data technology in urban planning, the requirements for data privacy are getting higher and higher . [0003] In the prior art, various privacy protections and reasonable desensitization have been attempted for the data to be analyzed. During this process, homomorphic encryption algorithms began to be introduced into urban planning to desensitize big data. [0004] Homomorphic encryption is a kind of encryption method with special natural properties. This concept was first proposed by Rivest et al. in the 1970s. Compared with general encryption algorithms, homomorphic encryption can not only realize basic encryption operations, but also A variety of calculation functions between ciphertexts c...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F21/62G06F21/60G06Q50/26
CPCG06F21/6245G06F21/602G06Q50/26
Inventor 周长林范小勇魏大鹏李刚
Owner 天津市城市规划设计研究总院有限公司
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