Ciphertext space keyword retrieval method and system for semantic comprehension

Abstract

The invention discloses a space keyword ciphertext retrieval method and system for semantic comprehension. The space keyword ciphertext retrieval system comprises a key module, a semantic informationextraction module, an encryption index construction module, a trap door generation module and a query module. By extracting the space objects and the semantic features queried by the user, the user can query the space objects which accord with the query intention of the user and are close to each other on the ciphertext. The ciphertext index construction mode adopted by the invention improves precision of ciphertext space keyword retrieval, and meets the query requirements of users for distance and text. In addition, the ciphertext query algorithm of the scheme improves query efficiency whileensuring the security and privacy of the space object data and the user retrieval information.

Description

technical field [0001] The invention relates to the technical field of searchable encryption, in particular to a semantically understood ciphertext space keyword retrieval method and system. Background technique [0002] Spatial keyword retrieval involves a large amount of spatial object data, and its query process requires a large amount of computing overhead. At this time, the data owner often chooses to outsource the spatial object data to the cloud server, and let the cloud server perform storage and calculation. However, since the data owner loses direct control over the outsourced data, data security and privacy cannot be guaranteed. In particular, the spatial object data contains sensitive information such as location coordinates, so it is essential to encrypt the spatial object data. [0003] The traditional spatial keyword query algorithm is only for plaintext data, and users cannot directly query the ciphertext data stored in the cloud server. Secondly, the trad...

AI Technical Summary

Problems solved by technology

However, this method only supports plaintext queries and cannot protect the privacy of data owners

[0005] Xidian University discloses a data ciphertext query method based on fine-grained sorting in a single user environment in its patent document "Data Encryption Query Method Based on Fine-grained Sorting in a Single User Environment". The disadvantage is that the semantic information in the data user query cannot be extracted, resulting in limited search accuracy

Its dimension is large, resulting in high computational overhead and low query efficiency

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