Safety 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 the problems of leaked data access mode, difficult balance between query service security and query cost, and susceptibility to reasoning attacks

Active Publication Date: 2019-01-11
NORTHEASTERN UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
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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 cip...

Method used

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  • Safety kNN query method based on LBS
  • Safety kNN query method based on LBS
  • Safety kNN query method based on LBS

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Embodiment Construction

[0152] The invention will be further described below in conjunction with the accompanying drawings and specific implementation examples, as figure 1 and image 3 As shown, the specific process includes:

[0153] Step 1. The data owner DO generates a key pair (pk, sk) and an encrypted index structure, wherein the generated Paillier key length is 1024 bits, and sends the encrypted index structure to the server C1, and sends the public key pk to Servers C1, C2 and user User send the private key sk to server C2. Use Gowalla to sign in the data set, and randomly select 1000 points for testing, use the point of interest POI as a data point, and standardize the data into a 16-bit large integer, each integer uses the data owner DO to use the processed data point as a seed For nodes, use Fortune's algorithm to build a Voronoi diagram, and then divide the grid to generate encrypted index structures SVD and SG;

[0154] The encrypted index structure includes: secure Voronoi diagram SVD...

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Abstract

The present invention belongs to the field of data privacy protection, and provides a safety kNN query method based on the LBS. The flows of the method comprise the steps of: generating a key pair andan encryption index structure by a data owner, sending the encryption index structure to a server C1, sending a public key to the server C1, a server C2 and a user, and sending a private key to the server C2; employing public key encryption to generate an encryption query request for the query of the user itself, and sending the query request to the server C1; after the server C1 obtains the encryption index structure and an encrypted query request, defining secure two party computation; based on the secure two party computation, designing a safety kNN query protocol; and returning a query result to a user. The safety kNN query method based on the LBS can effectively protect the privacy of data on the server, the privacy of the query request of the user, the privacy of the query result ofthe user and the access mode in the query process, and provides an accurate query result, is suitable for a mobile device with a lower processing capacity and greatly improves the speed completing the query.

Description

technical field [0001] The invention belongs to the field of data privacy protection, and in particular relates to a secure kNN query method based on LBS. Background technique [0002] In recent years, with the rapid development of mobile networks and smart phones, location-based services (LBS) have been widely used in various aspects such as social networking, life services, and online shopping. Among them, kNN query, that is, querying the k nearest neighbor points closest to the user's position, is a basic and representative important query. However, while LBS brings great convenience to our life, it also brings us the hidden danger of privacy leakage. From the perspective of user privacy, when performing a location-based query, the server can easily collect the user's real location while responding to the user's request, and infer private information such as religious belief, home address, and daily life trajectory from it. From the perspective of enterprises, many ente...

Claims

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Application Information

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IPC IPC(8): H04L29/06H04L9/08H04L9/00
CPCH04L9/008H04L9/0869H04L63/0428
Inventor 杨晓春王斌王雷霞
Owner NORTHEASTERN UNIV
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