A Hierarchical Clustering Framework for Secure and Efficient Ranked Keyword Search over Encrypted Cloud Data
Author
B. Raju, A Sai Koushik, MD. Afroz, K Srija
Abstract
Cloud data owners increasingly outsource documents in encrypted formats to protect sensitive information and maintain data privacy. However, traditional encryption mechanisms conceal inter-document semantic relationships, leading to severe degradation in search precision and retrieval performance. Furthermore, the exponential growth of data volume in cloud storage infrastructure creates a critical demand for high-speed, reliable ciphertext search schemes. To address these challenges, this paper proposes a multi-keyword ranked search architecture based on a hierarchical clustering index (MRSE-HCI). The proposed scheme dynamically clusters documents according to a minimum relevance threshold and recursively subdivides clusters until a maximum capacity constraint is met. In the search phase, this hierarchical organization reduces computational overhead to a linear rate even as document volume grows exponentially. To ensure search result integrity against malicious or corrupted cloud nodes, a minimum hash sub-tree structure is introduced for lightweight verification. Experimental evaluations on IEEE Xplore collection sets confirm that the proposed scheme achieves superior search efficiency, enhanced rank privacy, and high document retrieval relevance compared to conventional linear ciphertext search models.
Keywords
Cloud computing, ciphertext search, privacy-preserving search, ranked multi-keyword search, hierarchical document clustering, minimum hash sub-tree, search result verification, rank privacy.
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References
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