Efficient Indexing Method For Multi-Keyword Ranked Search For Encrypted Cloud Data Using E-TFIDF

Abstract

In Cloud Storage, data owners may also share their outsourced data with a large number of users who may need to best retrieve positive, reliable data documents that they are inquisitive about during a given session. One of the most common ways to do this is by looking for keywords. Such a keyword search method helps users to selectively retrieve documents of interest. Similar works on searchable encryption are primarily focused on the frequency of the occurrence of the keyword in the study. Documents that contain extra keyword-related records with less frequency of the prevalence of the keyword in the report may be available. In this paper, implement a method that recognizes such documents at the same time as returning the documents to the applicant's level. To maintain the security of the data, outsourced data is typically stored in a cloud server encryption form, making it incredibly difficult to search for unique encrypted documents that match those keywords on the cloud server for customers. To resolve this problem, use the Commonplace Enhanced-Term Frequency—Inverse Document Frequency (E-TFIDF) rule in this paper to measure the relevance scores of documents that fit the search request. The weighting of the results of the proposed E-TFIDF obtained the weight value significance of each article from the highest to the lowest weight. The overall success of the proposed approach is the product of the use of precision and recall.