As the information society advances swiftly, individuals and corporations are producing vast quantities of data daily. Cloud computing presents considerable strengths in storing and applying this data. Yet, challenges related to data security and privacy within cloud computing are obstructing its continued expansion. To guarantee data confidentiality, data owners (DOs) employ conventional cryptographic techniques to encrypt information prior to delegating it to cloud servers. However, this makes efficient search difficult to achieve. Searchable encryption (SE) can effectively alleviate this dilemma. However, most existing SE schemes have not fully considered spelling errors and semantic extension of keywords. At the same time, users’ personalized characteristics are not considered in the search process, and personalized retrieval services cannot be supported on encrypted data. The study designs an efficient and intelligent personalized search (EIPS) scheme based on user’s interest, which can intelligently conduct multikeyword precise search and fuzzy semantic search based on user’s interest model, and return accurate top-k search results. Our contribution consists of three aspects. First, this scheme combines precise search, fuzzy search, semantic expansion, and personalized search technology to realize intelligent personalized multikeyword search. Second, the use of vector cross matching and short-circuit matching effectively improves retrieval efficiency. Third, considering the protection of data privacy, a hybrid cloud server architecture was employed. Specifically, the user interest model (UIM) is stored on a private cloud server (PRCS), and the sorting of search results is also completed on the PRCS. This setting not only ensures the security of user data and computing operations but also reduces the burden on users. The security analysis results indicate that EIPS can ensure the privacy of data and users. The experimental results also show that this scheme has high efficiency while providing personalized search results for users.
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