Multi-keyword ciphertext storage and retrieval method and system based on word vectors

Abstract

The invention discloses a multi-keyword ciphertext storage and retrieval method and system based on word vectors. The method comprises the following steps: a data owner represents a keyword of a plaintext document as an (n+1)-dimensional word vector, calculates and uploads a ciphertext index and an encrypted document corresponding to the plaintext document to a cloud server, and sends an index key, a decryption private key and model parameters to a data user; and the data user inquires a keyword set to generate a trap door, obtains a plurality of encrypted documents with the highest relevancyfrom the cloud server side, and obtains corresponding plaintext documents through decryption. According to the method, the implicit semantics of the words can be accurately obtained through the word vectors, so that the query accuracy can be improved; and the thought of an MRSC method is used for reference, so that the ciphertext query safety is guaranteed, and background attacks of enemies are prevented.

Description

technical field [0001] The invention belongs to the field of ciphertext retrieval, in particular to a multi-keyword ciphertext storage and retrieval method and system based on word vectors. Background technique [0002] Driven by the rapid development of Internet applications, users' requirements for storage capacity are increasing day by day. Therefore, more and more enterprises or individuals (that is, data owners) will choose to store data on cloud servers to save local storage space. During this process, in order to ensure data security, the data owner will first encrypt the data before uploading it to the cloud server. Encrypted data will lose flexibility. If users want to obtain the required data from a large amount of encrypted data, they need to download and decrypt all the data on the cloud server before obtaining it. In this way, the efficiency of obtaining relevant data is very low. To solve this problem, researchers have proposed ciphertext retrieval technology....

AI Technical Summary

Problems solved by technology

On the basis of the MRSE method, subsequent researchers expanded the relevant words of the query keywords through technologies such as query expansion and personalized recommendation to increase the semantic information of the query keywords. The increase of words will cause the phenomenon of query semantic drift, which will lead to the problem of lower retrieval accuracy

[0005] Although the Chinese patent application CN109271485A discloses a semantic-supported cloud environment encrypted document ranking retrieval method, the LDA topic model adopted in this method only uses the probability distribution of keywords under specific topics to represent the keyword's relationship to topic semantics. Potential contribution, but it cannot fully and directly mine the semantic relationship of keywords, so the improvement of the accuracy of ciphertext retrieval by this application is still limited

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