EFURMS: An Efficient Scheme for File Upload and Ranked M ulti Keyword Search over Encrypted Data in Cloud

Cloud based services provide scalable storage capacities and enormous computing capability to enterp r ises and individuals to support big data operations in different sectors like banking, scientific research and health care. Therefore many data owners are interested to outsource their data to cloud storage servers due to their huge advantage in data proc e ssing. However, as the banking and health records usually contain sensitive data, there are privacy concerns if the data gets leaked to un trusted third parties in cloud storage. To protect data from leakage, the widely used technique is to encrypt the da t a before uploading into cloud storage servers. The traditional methods implemented by many authors consumes more time to outsource the data and searching for a document is also time consuming. Sometimes there may be chances of data leakage due to insuffic i ent security. To resolve these issues, in the current VPSearch(VPS) scheme is implemented, which provides features like verifiability of search results and privacy preservation. With its features the current system consumes more time for file uploading an d index generation, which slows down the searching process. In the existing VPS scheme time minimization to efficiently search for a particular document is a challenging task on the cloud. To resolve all the above drawbacks, we have designed an index gene r ation scheme using a tree structure along with a search algorithm using Greedy Depth first technique, that reduces the time for uploading files and file searching time. The newly implemented scheme minimizes the time required to form the index tree file f o r set of files in the document which are to be uploaded and helps in storing the files in a index tree format. These techniques result in reducing the document upload time and speeding up the process of accessing data efficiently using multi keyword searc h with top --'K' value.