Multi-Keyword Text Search with Merkle Hash Tree for Privacy Preservation over the Encrypted Data

In cloud computing, the end user stored their files with minimum maintenance cost, where cloud servers provide the file storage facility to analyze their outsourced data. However, security of the data is a major concern of the end user, because unauthorized person may access the data in cloud. The end-user should encrypt the files for providing data usability and privacy, before outsourcing to the cloud. The main aim of the research work is to secure the outsourced file data in cloud and only the end user can able to access those files from cloud storage system. This research aims to apply Merkle Hash Tree (MHT) to store the encrypted data with the hash value to increase the efficiency of the search process. The application of this method in cloud search engine to search the encrypted data with increasing retrieval efficiency. In multiuser system, to prevent the unauthorized access of data, fine-grained access control plays a major role in cloud. But, some authorized user may leak the secret key purposefully for financial benefits. To overcome these challenging issues, this research work implements the privacy-preserving Multi-keyword Text Search (MTS) with a similarity-based ranking method. Also, two secure index schemes namely known background and cipher text model are developed to enhance the search privacy. When compared with the linear search, the search efficiency is further improved by implementing the MHT. The experiments are conducted to validate the efficiency of the proposed method with existing techniques. The proposed MTS-MHT technique achieved 99.95% retrieval accuracy with minimum searching time (i.e. 80sec) for the various number of files, when compared with traditional encryption techniques.