Author(s): P .Muthamil Selvang, S.Sanjeev, G. Elatharasan

Abstract: Many data user are encouraged to outsource their data to cloud servers for great portable and reduced costs in data management which is increased popularity of cloud computing. However, sensitive data should be encrypted before outsourcing for privacy requirements, so the data use like keyword-based document retrieval. We present a secure and efficient multi-keyword ranked search scheme over encrypted data, which additionally supports dynamic update operations like deletion and insertion of documents. Explicitly, we construct an index tree based on vector space model and the used “term frequency (TF) X inverse document frequency (IDF)” model to provide multi-keyword search, which meanwhile supports flexible update operations. Then generates an encrypted document collection for plaintext document using the AES (Advanced Encryption Standard) algorithm. To improve search efficiency, we further propose a “Greedy Depth-first Search (GDFS)” algorithm based on tree-based index structure. The user can decrypt the encrypted documents with the shared secret key. With this approach, we can improve safe and search effectiveness.