An Efficient Multi Keyword Ranked Search over Encrypted Cloud Data

Abstract

Recently, more and more people are interested to outsource their local data to public cloud servers for great convenience and reduced costs in data management and security. But in fact of consideration privacy issues, sensitive data should be encrypted here before outsourcing, which obsoletes traditional data utilization like keyword-based document retrieval policy. In this project  proposed to make the clusters of similar documents based on the cosine values of the document vectors. We also proposed a MRSE model used to search the documents which are in encrypted form. The proposed search technique only finds the cluster of documents with the highest similarity value instead of searching on the whole dataset. Processing the dataset on two algorithms shows that the time needed to form the clusters in the proposed method is less. When the documents in the dataset increases, the time needed to form clusters also increases. The result of the search shows that increasing the documents also increases the search time of the proposed method.