IFS03-Semantic-aware Searching over Encrypted Data for Cloud

ABSTRACT:

With the increasing adoption of cloud computing, an increasing number of clients outsource their datasets to a cloud. To preserve privacy, the datasets are usually encrypted before outsourcing. Be that as it may, the common practice with regards to encryption makes the compelling use of the data difficulty. For instance, it is hard to look through the given keywords in encrypted datasets. Numerous plans are proposed to make encrypted data searchable based on keywords. In any case, keyword-based search schemes disregard the semantic representation data of clients’ recovery, and can’t totally meet with clients seek aim. In this manner, how to outline a substance based pursuit plan and make semantic search scheme more effective and context-aware is difficult to challenge. In this project, we propose ECSED, a novel semantic search scheme based on the concept of hierarchy and the semantic relationship between concepts in the encrypted datasets. ECSED utilizes two cloud servers. One is utilized to store the outsourced datasets and restore the positioned results to information clients. The other one is utilized to register the closeness scores between the reports and the question and send the scores to the first server. To additionally enhance the search effectiveness, we use a tree-based file structure to arrange all the document index vectors. We utilize the multi-catchphrase positioned seek over scrambled cloud information as our essential edge to propose two secure plans. The experiment results about based on this real-world datasets demonstrate that the plan is more efficient than past plans. We additionally demonstrate that our plans are secure under the known ciphertext model and the known background model.

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