Semantic-based multi-keyword sorting search privacy protection system and method

Abstract

The invention discloses a semantic-based multi-keyword sorting search privacy protection system and method, and relates to three entities: a cloud data owner, a cloud data user and a public cloud server. The cloud data owner performs grammar and lexical analysis on plaintext documents in a client to generate a keyword set, calculates domain weighted scores and correlation scores of keywords, generates plaintext document vectors, establishes document indexes through a hierarchical clustering algorithm, and reserves a relationship among the plaintext documents. The cloud data user performs semantic extension on input search keywords to generate a semantically extended word set, and performs vectorization and encryption to generate trap door query vectors. The public cloud server matches thetrap door query vectors with cluster center vectors. Therefore, the trap door query vectors are prevented from being matched with a large amount of ciphertext document vectors; and the retrieval efficiency is greatly improved.

Description

technical field [0001] The present invention relates to the field of information security, in particular to a semantic-based multi-keyword sorting search privacy protection system and method, which encrypts plaintext documents that need to be uploaded to the cloud to protect user privacy, and uses hierarchical clustering-based encrypted indexes and Trapdoor query is used to realize the search of encrypted documents, which improves the usability of ciphertext documents. Background technique [0002] As we enter the era of big data, a large amount of data is generated every day all over the world. Enterprises and users with large amounts of data usually choose to outsource their important data to cloud facilities to reduce data management costs and storage facility expenditures. Therefore, the data volume of cloud data is increasing rapidly. With the rapid development of cloud computing technology, more and more sensitive data are stored in the cloud, such as emails, private...

AI Technical Summary

Problems solved by technology

However, with the rapid growth of cloud data scale, this waste of a lot of time, bandwidth and power consumption obviously cannot meet the actual needs of users. Therefore, how to search for the required data in a large number of ciphertexts has become a difficult problem

[0004] Currently, some searchable encryption schemes have been proposed, such as a keyword-based symmetric encryption algorithm. When a user searches for a keyword, the search query operation needs to traverse the entire document. This method has a large time and space overhead; such as an encryption-based The document search method of the inverted index, which searches for documents through the inverted index, which improves the efficiency of the query, but can only be searched using a single keyword

Later, a method based on document vectors was proposed to search. Users can use multiple keywords to search, but these schemes require that the keywords entered by the user must completely match the predefined keywords before the search results can be returned, which makes the search scheme unique. Larger limitations

Moreover, in the environment of a large amount of data, it takes a lot of time to match document vectors one by one, so a search method with high retrieval efficiency is needed

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