Multiple Keywords Searching On Encrypted Cloud in Data Retrieval System

Rajeshwari Patil, Santosh Kumar


Cloud computing is a fast growing technology, so many users
rushed to adopt this latest technology. This technology make
data holder possible to outsource his/her data on cloud for the
public access. But information on cloud may contain sensitive
data so there is need to protect it. So the best way is Data
holder should encrypt data before uploading his data on cloud.
However this will significantly lower the usability of
outsourced data as it will be much harder for user to search for
query over encrypted data so to solve this problem the idea of
research is firstly to find relevant score of keywords, which
will enhance actual search of keywords. Secondly, research
will present very capable searching scheme which will include
multiple-keyword searching i.e. complex queries containing
logical operations can be searched. Thirdly, idea is to have
sophisticated indexing framework by categorizing subdictionaries
skills. Furthermore, research also aims at
providing fault tolerance to the system which is achieved by
sending notification to the data owner when unauthenticated
user try to edit data of data holder from cloud. System can be
used for any search engine or manly useful for big companies
or organizations where there is need to store large and
sensitive data. Thus, system will provide Fault tolerance and
an efficient multi-keyword retrieval over encrypted cloud

Full Text:



H. Liang, L. X. Cai, D. Huang, X. Shen, and D. Peng, A

smdp based service model for inter domain resource

allocation in mobile cloud networks, IEEE Transactions

on Vehicular Technology, vol. 61, no. 5,pp. 2222-2232,

M. M. Mahmoud and X. Shen, A cloud-based scheme for

protecting source-location privacy against hotspotlocating

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 polynomial evaluation, in

Proceedings of INFOCOM. IEEE, 2013, pp.2634-2642.

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,


A. Boldyreva, N. Chenette, Y. Lee, and A. Oneill, Orderpreserving

symmetric encryption, in Advances in

Cryptology-EUROCRYPT. Springer, 2009, pp. 224-241.

W. Sun, B. Wang, N. Cao, M. Li, W. Lou, Y. T. Hou,

and H. Li, Verifiable privacy-preserving multi-keyword

text search in the cloud supporting similarity-based

ranking, IEEE Transactions on Parallel and Distributed

Systems, vol. DOI: 10.1109/TPDS.2013.282, 2013.

J. Yu, P. Lu, Y. Zhu, G. Xue, and M. Li, Towards secure

multi keyword top-k retrieval over encrypted cloud data,

IEEE Transactions on Dependable and Secure

Computing, vol. 10, no. 4, pp. 239-250,2013.

A. Arvanitis and G. Koutrika, towards preference-aware

relational databases, in International Conference on Data

Engineering (ICDE).IEEE, 2012, pp. 426-437.

N. Ferguson, R. Schroeppel, and D. Whiting, A simple

algebraic representation of rijndael, in Selected Areas in

Cryptography. Springer, 2001, pp. 103-111.

Wang, N. Cao, K. Ren, and W. Lou, Enabling secure and

efficient ranked keyword search over outsourced cloud

data, IEEE Transactions on Parallel and Distributed

Systems, vol. 23, no. 8, pp. 1467-1479,2012.

P. Golle, J. Staddon, and B. Waters, Secure conjunctive

keyword search over encrypted data, in Applied

Cryptography and Network Security. Springer, 2004, pp.


D. Boneh and B. Waters, Conjunctive, subset, and range

queries on encrypted data, in Theory of cryptography.

Springer, 2007, pp. 535-554.

D. Boneh, G. Di Crescenzo, R. Ostrovsky, and G.

Persiano, Public key encryption with keyword search, in

Advances in Cryptology Eurocrypt. Springer, 2004, pp.


Q. Liu, C. C. Tan, J. Wu, and G. Wang, Efficient

information retrieval for ranked queries in cost-effective

cloud environments, in Proceedings of INFOCOM.

IEEE, 2012, pp. 2581-2585.

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.

S. Zerr, E. Demidova, D. Olmedilla, W. Nejdl, M.

Winslett, and S. Mitra, “Zerber: r-confidential indexing

for distributed documents,” in Proceedings of the 11th

international conference on Extending database

technology: Advances in database technology. ACM,

, pp. 287–298.

W. K. Wong, D. W.-l. Cheung, B. Kao, and N.

Mamoulis, Secure knn computation on encrypted

databases, in Proceedings of SIGMOD International

Conference on Management of data. ACM, 2009,



  • There are currently no refbacks.

Copyright © IJETT, International Journal on Emerging Trends in Technology