HCSF: A hierarchical clustering algorithm based on swarm intelligence and fuzzy logic for ciphertext search

Abstract

With the demand of data security, ciphertext search is becoming a popular issue. Especially, the efficiency of ciphertext search is attracting more and more attention as the data volume is experiencing explosive growth. Traditional search methods are not suitable for current situation since all the data stored at the cloud server is encrypted. Therefore, this paper proposes a hierarchical clustering algorithm based on swarm intelligence and fuzzy logic (HCSF) to address the efficiency problem in ciphertext search. The proposed method classifies different documents into different categories by taking the advantage of swarm intelligence and fuzzy logic. Meanwhile, a split mechanism based on the maximum of documents in a cluster is proposed to deal with some clusters containing excessive documents. Furthermore, a hierarchical structure is designed to organize the documents by combining with the split mechanism. An experiment built on the 20 Newsgroups data set is conducted to assess the efficiency of HCSF. The experimental result shows the proposed method is efficient.