(untitled) (Lex localis - Journal of Local Self-Government, 2025)
Cloud servers have become a preferred platform for individuals and organizations to outsource and manage data. However, protecting sensitive information through encryption creates challenges for effective data retrieval. Traditional search methods mainly rely on exact keyword matching, which limits usability when dealing with synonyms or misspellings. To address this issue, this study proposes a novel fuzzy keyword ranked search framework for encrypted cloud data. The approach integrates a fuzzy logic wordbook to expand search terms, include synonyms, and handle spelling variations. In the data owner phase, documents are encrypted using the ERA algorithm, while index tables are generated through preprocessing, clustering (IFFC), summarization (LSA), and score calculation (ASC). Both the documents and the index tables are further protected using ERA encryption and freshness is maintained with the SHA-516 algorithm. During the DU phase, the WFKS method facilitates secure and ranked document retrieval from the CSP. Experimental evaluation demonstrates that the proposed method achieves faster, more accurate, and more secure retrieval compared with existing techniques, thereby improving efficiency and privacy in encrypted cloud environments.