The extensive use of cloud services has resulted in dramatic growth in volume of data which has made information retrieval much more difficult than before. Even text documents are encrypted before being outsourced to cloud servers. This helps to protect user’s data privacy. Existing techniques to search over encrypted data are not suitable for a huge data environment. Due to the blind encryption, relationship between the documents is concealed which further leads to search accuracy performance degradation. Therefore it is necessary to adopt an approach to support more search semantic and for fast search within enormous data. A hierarchical clustering method for cipher text search is proposed in this paper. The proposed approach clusters the documents based on the minimum similarity threshold, and then partitions the resultant clusters into sub-clusters until the constraint on the maximum size of cluster is reached. The very first thing which cloud server does is that it performs search activity and then selects the k documents (previously decided by the user and sent to the cloud server) from the minimum desired sub-category. To request desired documents, instead of using single keyword search query, multi-keyword search technique is proposed.