KGRAM-BASED COMPOSITE SECRET SIGN SEARCH OVER ENCRYPTED CLOUD INFORMATION

Computer Science and Engineering

A Large number of data owners have moved our data into cloud servers. Cloud data owners prefer to outsource documents in an encrypted form for the function of confidentiality preserving. Therefore it is essential to develop efficient and reliable cipher text search method. One challenge is that the relationship between documents will be normally concealed in the procedure of encryption, which will lead to major search accuracy performance degradation. All access the data from cloud by using the keyword based search. The secure multi-keyword ranked search from the encrypted data from the cloud, top-k search problem for big data encryption against privacy breaches, and attempt to identify an efficient and secure solution to this problem. It accessible operations like update, delete, insertion of documents. Here using tree structure and nebulous search method for retrieve the data from the cloud. These types of techniques are used to solve the problem of keyword guessing attack. The blowfish algorithm for the encryption process. We propose a group multi-keyword top-k search scheme based on the idea of partition, where a group of tree-based indexes are constructed for all documents. We combine these methods together into an efficient and secure approach to address our proposed top-k similarity search here to reduce statistical attacks. The extensive experimental results on real-life data sets demonstrate that our approach can significantly improve the capability of defending the privacy breaches, the scalability and the time efficiency of query processing over the state-of-the-art methods. It can achieve sub-linear search time and the search result like a number of file retrieval also deal with deletion and insertion of documents flexibly.

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.