Enabling Fine-grained Multi-keyword Search Supporting Classified Sub-dictionaries over Encrypted Cloud Data
G.Lucy, D.Jaya Narayana Reddy, R.Sandeep Kumar, ,
Affiliations Pursuing M.Tech, CSE Branch, Dept of CSEAssistant Professor, Department of Computer Science and Engineering</br>Assistant Professor, Department of Computer Science and Engineering G.Pullaiah College of Engineering and Technology, Kurnool, Andhra Pradesh, India.
Utilizing Cloud Computing, people can store their information on remote servers and permit information
access to open clients through the cloud servers. As the outsourced information are liable to contain touchy protection data,
they are regularly scrambled before transferred to the cloud. This, on the other hand, altogether restrains the ease of use of
outsourced information because of the trouble of seeking over the encoded information. In this paper, we address this issue
by building up the fine-grained multi-watchword hunt plans over scrambled cloud information. Our unique commitments are
three-fold. To begin with, we present the significance scores and inclination elements upon watchwords which empower the
exact catchphrase seek and customized client experience. Second, we build up a handy and exceptionally effective multicatchphrase inquiry plan. The proposed plan can backing entangled rationale seek the blended "AND", "OR" and "NO"
operations of catchphrases. Third, we further utilize the ordered sub-lexicons procedure to accomplish better proficiency on
list building, trapdoor producing and question. Finally, we examine the security of the proposed plans as far as secrecy of
reports, security assurance of file and trapdoor, and unlinkability of trapdoor. Through broad investigations utilizing this
present reality dataset, we approve the execution of the proposed plans. Both the security examination and test results
show that the proposed plans can accomplish the same security level contrasting with the current ones and better execution
as far as usefulness, question multifaceted nature and effectiveness.
G.Lucy,D.Jaya Narayana Reddy,R.Sandeep Kumar."Enabling Fine-grained Multi-keyword Search Supporting Classified Sub-dictionaries over Encrypted Cloud Data". International Journal of Computer Engineering In Research Trends (IJCERT) ,ISSN:2349-7084 ,Vol.2, Issue 12,pp.919-923, December- 2015, URL :https://ijcert.org/ems/ijcert_papers/V2I1220.pdf,
 H. Liang, L. X. Cai, D. Huang, X. Shen, and D. Peng, “An smdp-based service model for interdomain resource allocation in mobile cloud networks,” IEEE Transactions on Vehicular Technology, vol. 61, no. 5, pp. 2222–2232, 2012.
 M. M. Mahmoud and X. Shen, “A cloud-based scheme for protecting source-location privacy against hotspot-locating attack in wireless sensor networks,” IEEE Transactions on Parallel and Distributed Systems, vol. 23, no. 10, pp. 1805–1818, 2012.
 Q. Shen, X. Liang, X. Shen, X. Lin, and H. Luo, “Exploiting geo-distributed clouds for e-health monitoring system with minimum service delay and privacy preservation,” IEEE Journal of Biomedical and Health Informatics, vol. 18, no. 2, pp. 430–439, 2014.
 T. Jung, X. Mao, X. Li, S.-J. Tang, W. Gong, and L. Zhang, “Privacy-preserving data aggregation without secure channel: multivariate poly-nomial evaluation,” in Proceedings of INFOCOM. IEEE, 2013, pp. 2634–2642.
 Y. Yang, H. Li, W. Liu, H. Yang, and M. Wen, “Secure dynamic searchable symmetric encryption with constant document update cost,” in Proceedings of GLOBCOM. IEEE, 2014, to appear.
 N. Cao, C. Wang, M. Li, K. Ren, and W. Lou, “Privacy-preserving multi-keyword ranked search over encrypted cloud data,” IEEE Transactions on Parallel and Distributed Systems, vol. 25, no. 1, pp. 222–233, 2014.
 https://support.google.com/websearch/answer/173 733?hl=en.
 D. X. Song, D. Wagner, and A. Perrig, “Practical techniques for searches on encrypted data,” in Proceedings of S&P. IEEE, 2000, pp. 44–55.
 R. Li, Z. Xu, W. Kang, K. C. Yow, and C.-Z. Xu, “Efficient multi-keyword ranked query over encrypted data in cloud computing,” Future Generation Computer Systems, vol. 30, pp. 179– 190, 2014.
 H. Li, D. Liu, Y. Dai, T. H. Luan, and X. Shen, “Enabling efficient multi-keyword ranked search over encrypted cloud data through blind storage,” IEEE Transactions on Emerging Topics in Computing, 2014, DOI10.1109/TETC.2014.2371239.
 C. Wang, N. Cao, J. Li, K. Ren, and W. Lou, “Secure ranked keyword search over encrypted cloud data,” in Proceedings of ICDCS. IEEE, 2010, pp. 253–262.
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