An Efficient and Secure Multi Keyword Search in Encrypted Cloud Data with Ranking

As cloud computing become more flexible & effective in terms of economy, data owners are motivated to outsource their complex data systems from local sites to commercial public cloud. But for security of data, sensitive data has to be encrypted before outsourcing, which overcomes method of traditional data utilization based on plaintext keyword search. Considering the large number of data users and documents in cloud, it is necessary for the search service to allow multikeyword query and provide result similarity ranking to meet the effective data retrieval need. Retrieving of all the files having queried keyword will not be affordable in pay as per use cloud paradigm. In this paper, we propose the problem of Secured Multikeyword search (SMS) over encrypted cloud data (ECD), and construct a group of privacy policies for such a secure cloud data utilization system. From number of multi-keyword semantics, we select the highly efficient rule of coordinate matching, i.e., as many matches as possible, to identify the similarity between search query and data , and for further matching we use inner data correspondence to quantitatively formalize such principle for similarity measurement. We first propose a basic Secured multi keyword ranked search scheme using secure inner product computation, and then improve it to meet different privacy requirements. The Ranked result provides top k retrieval results. Also we propose an alert system which will generate alerts when unauthorized user tries to access the data from cloud, the alert will generate in the form of mail and message. Keywords— Encryption, Inner product similarity, Multi-keyword search, ranking.