Multiple Keywords Searching On Encrypted Cloud in Data Retrieval System
Abstract
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
data.
Full Text:
PDFReferences
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,
,DOI10.1109/TETC.2014.237-1239.
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.
-45.
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.
-522.
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.
http://kdd.ics.uci.edu/databases/nsfabs/nsfawards.html.
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,
pp.139-152.
Refbacks
- There are currently no refbacks.
Copyright © IJETT, International Journal on Emerging Trends in Technology