Affiliations Pursuing M.Tech, CSE Branch, Dept of CSEAssistant Professor, Department of Computer Science and EngineeringAssistant Professor, Department of Computer Science and Engineering G.Pullaiah College of Engineering and Technology, Kurnool, Andhra Pradesh, India.
The major aim of this paper is to solve the problem of multi-keyword ranked search over
encrypted cloud data (MRSE) at the time of protecting exact method wise privacy in the cloud computing
concept. Data holders are encouraged to outsource their difficult data management systems from local
sites to the business public cloud for large flexibility and financial savings. However for protecting data
privacy, sensitive data have to be encrypted before outsourcing, which performs traditional data
utilization based on plaintext keyword search. As a result, allowing an encrypted cloud data search
service is of supreme significance. In view of the large number of data users and documents in the cloud,
it is essential to permit several keywords in the search demand and return documents in the order of their
appropriate to these keywords. Similar mechanism on searchable encryption makes centre on single
keyword search or Boolean keyword search, and rarely sort the search results. In the middle of various
multi-keyword semantics, deciding the well-organized similarity measure of “coordinate matching,” it
means that as many matches as possible, to capture the appropriate data documents to the search
query. Particularly, we consider “inner product similarity” i.e., the amount of query keywords shows in a
document, to quantitatively estimate such match measure that document to the search query. Through
the index construction, every document is connected with a binary vector as a sub index where each bit
characterize whether matching keyword is contained in the document. The search query is also
illustrates as a binary vector where each bit means whether corresponding keyword appears in this
search request, so the matched one could be exactly measured by the inner product of the query vector
with the data vector. On the other hand, directly outsourcing the data vector or the query vector will break
the index privacy or the search privacy. The vector space model facilitate to offer enough search
accuracy, and the DES encryption allow users to occupy in the ranking while the popularity of computing
work is done on the server side by process only on cipher text. As a consequence, data leakage can be
eradicated and data security is guaranteed.
A.Raghavendra Praveen Kumar,K.Tarakesh,U.Veeresh."A Secure and Dynamic Multi Keyword Ranked Search Scheme over encrypted". International Journal of Computer Engineering In Research Trends (IJCERT) ,ISSN:2349-7084 ,Vol.2, Issue 12,pp.1137-1141, December- 2015, URL :https://ijcert.org/ems/ijcert_papers/V2I1257.pdf,
Keywords : Multi-keyword ranked search over encrypted cloud data, OTP, Product resemblance,
Cloud, Data owners
 N. Cao, C. Wang, M. Li, K. Ren, and W. Lou, “Privacy-Preserving Multi-Keyword Ranked Search over Encrypted Cloud Data,” Proc. IEEE INFOCOM, pp. 829- 837, Apr, 2011.
 L.M. Vaquero, L. Rodero-Merino, J. Caceres, and M.Lindner, “A Break in the Clouds: Towards a Cloud Definition,” ACM SIGCOMM Comput. Commun. Rev., vol. 39, no. 1, pp. 50-55, 2009.
 N. Cao, S. Yu, Z. Yang, W. Lou, and Y. Hou, “LT Codes-Based Secure and Reliable Cloud Storage Service,” Proc. IEEE INFOCOM, pp. 693- 701, 2012.
 S. Kamara and K. Lauter, “Cryptographic Cloud Storage,” Proc. 14th Int’l Conf. Financial Cryptograpy and Data Security, Jan. 2010.
 A. Singhal, “Modern Information Retrieval: A Brief Overview,” IEEE Data Eng. Bull., vol. 24, no. 4, pp. 35- 43, Mar. 2001.
 I.H. Witten, A. Moffat, and T.C. Bell, Managing Gigabytes: Compressing and Indexing Documents and Images. Morgan Kaufmann Publishing, May 1999.
 D. Song, D. Wagner, and A. Perrig, “Practical Techniques for Searches on Encrypted Data,” Proc. IEEE Symp. Security and Privacy, 2000.
 E.-J. Goh, “Secure Indexes,” Cryptology ePrint Archive, http:// eprint.iacr.org/2003/216. 2003.  Y.-C. Chang and M. Mitzenmacher, “Privacy Preserving Keyword Searches on Remote Encrypted Data,” Proc. Third Int’l Conf. Applied Cryptography and Network Security, 2005.
 R. Curtmola, J.A. Garay, S. Kamara, and R. Ostrovsky, “Searchable Symmetric Encryption: Improved Definitions and Efficient Constructions,” Proc. 13th ACM Conf. Computer and Comm. Security (CCS ’06), 2006.
 D. Boneh, G.D. Crescenzo, R. Ostrovsky, and G. Persiano, “Public Key Encryption with Keyword Search,” Proc. Int’l Conf. Theory and Applications of Cryptographic Techniques (EUROCRYPT), 2004.
 M. Bellare, A. Boldyreva, and A. ONeill, “Deterministic and Efficiently Searchable Encryption,” Proc. 27th Ann. Int’l Cryptology Conf. Advances in Cryptology (CRYPTO ’07), 2007.
 M. Abdalla, M. Bellare, D. Catalano, E. Kiltz, T. Kohno, T. Lange, J. Malone-Lee, G. Neven, P. Paillier, and H. Shi, “Searchable Encryption Revisited: Consistency Properties, sRelation to Anonymous Ibe, and Extensions,” J. Cryptology, vol. 21, no. 3, pp. 350-391, 2008.
We have kept IJCERT is a free peer-reviewed scientific journal to endorse conservation. We have not put up a paywall to readers, and we do not charge for publishing. But running a monthly journal costs is a lot. While we do have some associates, we still need support to keep the journal flourishing. If our readers help fund it, our future will be more secure.