A Novel Searchable Attribute‐Based Encryption Scheme Supporting Fuzzy Keywords Ranking for the Cloud Environment

ABSTRACT The rapid advancement of cloud computing and big data has led to an increasing number of data owners seeking to outsource encrypted data to cloud servers. Searchable encryption (SE) is recognized as a crucial cryptographic primitive for data owners to retrieve data in this context. However, most current SE schemes suffer from low keyword search accuracy and an inability to verify search results. Additionally, encrypted data should be shared with specific data users without compromising their privacy. Therefore, this article introduces a novel fuzzy keyword‐enabled ranked searchable ciphertext‐policy attribute‐based encryption (FKRSCPABE) scheme to address these challenges. First, we combine ciphertext‐policy attribute‐based encryption (CP‐ABE) and public‐key encryption with keyword search (PEKS) to realize fine‐grained access control and efficiently search outsourced encrypted data for data owners. Second, since the document almost certainly contains typographical errors, we implement fuzzy keyword search to ensure meaningful and accurate results. Additionally, we employ probabilistic trapdoors to resist distinguishability attacks. Furthermore, we rank documents using weighted regional scores to improve search accuracy. As a result, our scheme achieves IND‐CCA security by using the classic Canetti transformation. In brief, our scheme is able to achieve fuzzy keyword search and better ranking of search results, while also ensuring data security.

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Publication Details

Journal
Concurrency and Computation Practice and Experience
Published
2025-12-11
DOI
https://doi.org/10.1002/cpe.70479
Primary Topic
Cryptography and Data Security
Type
article
Field-Weighted Citation Impact
0.00
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article

A Novel Searchable Attribute‐Based Encryption Scheme Supporting Fuzzy Keywords Ranking for the Cloud Environment

Gangqi Shu, Haibo Hong, Mande Xie, Yiyang Liu et al.
Concurrency and Computation Practice and Experience
Cryptography and Data Security
article

A Novel Searchable Attribute‐Based Encryption Scheme Supporting Fuzzy Keywords Ranking for the Cloud Environment

Gangqi Shu, Haibo Hong, Mande Xie, Yiyang Liu, Yihan Wu, Zichu Ren
article en

Abstract

ABSTRACT The rapid advancement of cloud computing and big data has led to an increasing number of data owners seeking to outsource encrypted data to cloud servers. Searchable encryption (SE) is recognized as a crucial cryptographic primitive for data owners to retrieve data in this context. However, most current SE schemes suffer from low keyword search accuracy and an inability to verify search results. Additionally, encrypted data should be shared with specific data users without compromising their privacy. Therefore, this article introduces a novel fuzzy keyword‐enabled ranked searchable ciphertext‐policy attribute‐based encryption (FKRSCPABE) scheme to address these challenges. First, we combine ciphertext‐policy attribute‐based encryption (CP‐ABE) and public‐key encryption with keyword search (PEKS) to realize fine‐grained access control and efficiently search outsourced encrypted data for data owners. Second, since the document almost certainly contains typographical errors, we implement fuzzy keyword search to ensure meaningful and accurate results. Additionally, we employ probabilistic trapdoors to resist distinguishability attacks. Furthermore, we rank documents using weighted regional scores to improve search accuracy. As a result, our scheme achieves IND‐CCA security by using the classic Canetti transformation. In brief, our scheme is able to achieve fuzzy keyword search and better ranking of search results, while also ensuring data security.

Concurrency and Computation Practice and ExperienceVol. 38(1)
Zhejiang Gongshang University (CN)
Openalex Percentile: Top 79%
Cryptography and Data Security
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A Novel Searchable Attribute‐Based Encryption Scheme Supporting Fuzzy Keywords Ranking for the Cloud Environment — Gangqi Shu, Haibo Hong, et al. · Concurrency and Computation Practice and Experience (2025) | TGRS Research Map | TGRS