An Efficient Storage and Retrieval Method Based On Multi-Key Ranked Search & Improved Hierarchical Clustering Index for Cloud Data

In this current scenario, computer technologies are getting change day by day. The cost of computing resources are extremely high and it is quite difficult to upgrade hardware’s software. Now users are demanding more innovative technologies which can provide optimum utilization of computing resources and cloud computing is one of them. Cloud computing in an improved form of various existing technologies such as grid computing, cluster computing, and distributed computing. Cloud computing serves computing resources such as PaaS, IaaS, and SaaS to cloud users on demand and ‘pay peruses’ based. A cloud user can store their private and essential data over the cloud and can retrieve any time. Day by day the number of cloud users and the size of cloud data are getting increases. Cloud service providers have to ensure the data privacy and integrity as well availability of stored data. Various cloud researchers are working on cloud data security and efficient retrieval. In this work, we are presenting an efficient data storage and retrieval method for encrypted data based on multi-keyword ranked search by improved hierarchical clustering index for cloud data to improve cloud performance. The proposed method basically takes place in two phases. In first phase IAES-256 bit data encryption and decryption methods are used to maintain data security and SHA-1 method is used to calculate the hash values of the message to maintain the data integrity and second phase uses efficient data retrieval method based on multi-keyword ranked search by improved hierarchical clustering index (by dynamic K-mean) with bagging approach for cloud data. Bagging provides a predictive probabilistic model which reduces the noise and irrelevant data during classification, which improves the accuracy. The proposed method uses an “In order” to verify the authenticity of search results, a structure called minimum hash sub-tree. Proposed method (MRSE-IHCI With bootstrap) and existing method (MRSE-HCI) both are implemented and compared based on various performance measuring parameters such as encryption time and storage, retrieval time and search time. Experimental result analysis clearly shows that proposed method performs outstanding over existing data storage and retrieval method for cloud data.