Efficient, flexible and verifiable multi-attribute range retrieval method and system in cloud environment

Abstract

The invention belongs to the technical field of cloud environment security, and discloses an efficient, flexible and verifiable multi-attribute range retrieval method and system in a cloud environment, a data owner establishes a plurality of index trees and an index lookup table for lookup of the index trees; the data owner generates a key and shares the key to the authorized user; the data owner encrypts the index tree, the index lookup table and the file data and uploads the encrypted data to a cloud server; the data authorization user generates a threshold; the cloud server selects an index tree for query according to the query identifier, and returns a query result to the authorized user; the authorized user decrypts the data and verifies whether the data is correct; the data owner updates the index lookup table and adds or deletes the corresponding index tree in the index lookup table; and the data owner updates the index tree, and adds, modifies or deletes the index in the sub-node of the index tree leaf. The disk access frequency and the index occupied space are reduced, the query efficiency is improved, and the dynamic range search requirement is met.

Description

technical field [0001] The invention belongs to the technical field of cloud environment security, and in particular relates to an efficient, flexible and verifiable multi-attribute range retrieval method and system in a cloud environment. Background technique [0002] At present, users can enjoy high-performance storage and computing services while paying a lower cost by using "cloud computing", and "cloud computing" service providers also greatly save management costs through unified management of computing resources , improving the utilization of computing resources. However, due to privacy concerns, data owners encrypt sensitive data before outsourcing, which in turn makes data exploitation a challenging issue. Therefore, it is very important to develop efficient privacy-preserving search systems on encrypted cloud data. The most common search method is to use keywords to retrieve files instead of downloading all encrypted files locally for retrieval. In order to sear...

AI Technical Summary

Problems solved by technology

[0008] (1) In the existing searchable encryption method for range query based on the bucket scheme, if the bucket range is too large, the returned result is too large to waste a lot of bandwidth resources and there will be too much useless information in the query result, making the search function impossible It is reflected; if the bucket range is too small, the privacy of the data will be seriously weakened; when the number of buckets is not much different from the number of data, it is easy to estimate the characteristics of the data through the characteristics of the buckets

[0009] (2) In the existing searchable encryption method based on the range query of the order-preserving scheme, only the range search of a single attribute is supported, and there are disadvantages such as the ciphertext cannot be updated, the index is too large, etc.

[0010] (3) The existing technical solution can only query the intersection of data satisfying multiple attributes, and the search method of the existing technical solution is still lacking in usability, and cannot meet user needs in some scenarios

[0012] The significance of solving the above problems and defects is: Although the ciphertext retrieval technology is very mature and the people's demand for data privacy is getting higher and higher, there are still few practical applications. The main reason is that the current research mainly pursues security and Efficiency ignores the actual application scenarios. Solving the above problems can make the application of ciphertext search technology closer to actual needs, broaden the application scenarios of ciphertext retrieval, and reduce the disk space usage and I / O load of cloud servers.

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