![]() Recently, some dynamic schemes have been proposed to support inserting and updating operations on document collection. Secure inner product computation was adopted in order to set strict privacy requirement to ensure secrecy of cloud communication. In order to secure and get the most relevant results retrieval, MRSE was adapted from secure k-nearest neighbor (kNN) technique to select the k nearest database records between database record and query vector. The main idea of this scheme was to allow users on search request and return documents with semantic multiple keywords. Multi-keyword ranked search over encrypted cloud data (MRSE) was introduced in 2014 by N. A general approach to protect the data confidentiality is to encrypt the data before outsourcing. ![]() The cloud service providers (CSPs) that keep the data for users may access users sensitive information without authorization. Despite of various advantages of cloud computing services ,outsourcing sensitive information like e-mails, personal health records ,government data or documents to remote servers have always privacy concerns. Because of these appealing features of cloud computing ,both individuals and enterprises are motivated to outsource their data to the cloud. INTRODUCTION Cloud computing has been emerged as a new model of IT infrastructure, which helps to organize huge resource of computing, storage and applications, and enable users to enjoy convenient and on demand network access to a shared pool of computing resources with great efficiency and minimal economic overhead. Index Terms: Cloud Computing, Multi keyword rank search scheme ,TF ,KNN algorithm, Greedy DFS algorithm I. Due to the use of our special tree-based index structure, the proposed scheme can achieve sub-linear search time and deal with the insertion and updating of documents flexibly. In order to calculate the TF value of the search keyword we use a pattern matching algorithm which indicates the occurrence of that particular keyword in a file. The secure kNN algorithm is utilized to encrypt the index and query vectors, and meanwhile ensure accurate relevance score i.e keyword weitage calculation between encrypted index and query vectors. Specifically, We construct a special tree-based index structure and propose a "Greedy Depth-first Search" algorithm to provide efficient multi-keyword ranked search. In this project, we present a secure multi keyword ranked search scheme over encrypted cloud data, which simultaneously supports dynamic update operations insertion and updating of documents. However, sensitive data should be encrypted before outsourcing for privacy requirements, which no longer support data utilization like keyword-based document retrieval. Due to the increasing popularity of cloud computing, more and more data owners are motivated to outsource their data to cloud servers for great convenience and reduced cost in data management.
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