A secure knn query method based on lbs

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...

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

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