A secure knn query method based on lbs

A query method and secure two-party computing technology, applied in the field of data privacy protection, can solve problems such as large time cost, difficult balance between query service security and query cost, leaked data access mode, etc., and achieve the effect of avoiding reasoning attacks

Active Publication Date: 2021-06-01
NORTHEASTERN UNIV LIAONING
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the intermediate results of encrypted calculations can still reveal the data access mode, that is, which data is accessed, which is often vulnerable to reasoning attacks
At the same time, in this process, the server needs to calculate on the ciphertext to obtain the query result. However, due to the complexity of the ciphertext calculation, the current proposed method often needs to consume a large time cost, which makes the security of the query service It is difficult to balance with the query cost

Method used

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  • A secure knn query method based on lbs
  • A secure knn query method based on lbs
  • A secure knn query method based on lbs

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Embodiment Construction

[0152]Further explanation will be further described below with reference to the accompanying drawings and specific embodiments, such asfigure 1 versusimage 3 As shown, specific processes include:

[0153]Step 1, the data owner DO generates a key pair (PK, SK), and encryption index structure, where the generated paillier has a key length of 1024 bits, and transmits the encrypted index structure to the server C1, send the public key PK. Servers C1, C2, and User User, send private key SK to the server C2. Use GOWALLA to check in the data set, and randomly select 1000 points to test, the points point POI is used as the data point, and the data is standardized to 16-bit large integers, each integer is used to use the data owner DO to process the processed data point as a seed Node, use Fortune's Algorithm to build a Voronoi diagram, then grid divide, generate an encrypted index structure SVD and SG;

[0154]The encryption index structure includes: secure Voronoi map SVD and security grid divid...

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Abstract

The invention belongs to the field of data privacy protection, and proposes a LBS-based secure kNN query method. The process includes: a data owner generates a key pair and an encrypted index structure, sends the encrypted index structure to a server C1, and sends a public key to the server C1, C2 and the user send the private key to the server C2; the user uses public key encryption to generate an encrypted query request for his own query, and sends the query request to the server C1; the server C1 obtains the encrypted index structure and encrypted query After the request, define the secure two-party calculation; design the secure kNN query protocol based on the secure two-party calculation; return the query result to the user; the present invention effectively protects the privacy of the data on the server, the privacy of the user's query request, and the privacy of the user's query result , the access mode in the query process, and provide accurate query results, suitable for mobile devices with low processing capabilities, and greatly improve the speed of completing the query.

Description

Technical field[0001]The present invention belongs to the field of data privacy protection, and is specifically involved in the LBS-based security KNN query method.Background technique[0002]In recent years, with the rapid development of mobile networks and smartphones, the location-based service (LBS) has a wide range of applications in social, life services, online shopping, etc. Among them, Knn queries, that is, the Query distance from the user location is a foundation and representative query. However, while LBS brought us great life, LBS also brought us privacy leaks. From the perspective of user privacy, when performing location-based queries, the server can easily collect user's true locations while responding to user requests, and inference from privacy information such as religious beliefs, home address, daily life trajectory. From the perspective of the company, many companies have enabled data to third-party servers through data outsourcing, and by third-party servers to c...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04L29/06H04L9/08H04L9/00
CPCH04L9/008H04L9/0869H04L63/0428
Inventor 杨晓春王斌王雷霞
Owner NORTHEASTERN UNIV LIAONING
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