Secure Semantic Retrieval over Encrypted Cloud Data: A Dual-Index System with Lightweight Fuzzy Encryption and BERT-Based Semantic Indexing

Cloud storage is widely used for store a personalized and Sensitive information. Cloud usually stores the files in encrypted mode. To search a user specific file among the encrypted files is difficult. Traditional keyword search may be fails when users phrase differently. Typos and vocabulary differences further reduce accuracy. Existing encrypted search solutions typically trade security for search quality. To address this gap, this work introduces a dual-index encrypted search system. This system combines exact keyword matching with semantic understanding. A keyword index, protected with LFEHI model. It supports fuzzy matching for small typing error. A semantic index built with BERT captures meaning and organizes embeddings in a kd-tree for fast retrieval. During a search, both indexes run in parallel. The encrypted keywords match through the hash index, and a semantic embedding check for related concepts. A 70/30 keyword-to-semantic weight is used to integrate their results. To ensuring that exact matches continue to be given priority. Tests on 1,000 documents and 300 queries show clear improvements. The system reaches 90.2% recall—22% higher than keyword-only search and it handles single-character typos with 94.6% accuracy. Average query time stays below 64 ms, supporting real-time use, and the storage cost is only 18.5%. There is no evidence s of content leakage or query leakage following a security evaluation. Due to the dual-index design, encrypted search can deliver meaningful understanding without compromising speed and security.