Advanced SearchSearch Tips
Efficient Top-K Queries Computation for Encrypted Data in the Cloud
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
 Title & Authors
Efficient Top-K Queries Computation for Encrypted Data in the Cloud
Kim, Jong Wook;
  PDF(new window)
With growing popularity of cloud computing services, users can more easily manage massive amount of data by outsourcing them to the cloud, or more efficiently analyse large amount of data by leveraging IT infrastructure provided by the cloud. This, however, brings the security concerns of sensitive data. To provide data security, it is essential to encrypt sensitive data before uploading it to cloud computing services. Although data encryption helps provide data security, it negatively affects the performance of massive data analytics because it forbids the use of index and mathematical operation on encrypted data. Thus, in this paper, we propose a novel algorithm which enables to efficiently process a large amount of encrypted data. In particular, we propose a novel top-k processing algorithm on the massive amount of encrypted data in the cloud computing environments, and verify the performance of the proposed approach with real data experiments.
Cloud Computing;Encryption;Top-k Query;
 Cited by
C. Orencik and E. Savas, “Efficient and Secure Ranked Multi-keyword Search on Encrypted Cloud Data,” Proceedings of the 2012 Joint EDBT/ ICDT Workshops, pp. 186-195, 2012.

Z. Xu, W. Kang, R. Li, K. Yow, and C.Z. Xu, “Efficient Multi-Keyword Ranked Query on Encrypted Data in the Cloud,” Proceeding of IEEE 18th International Conference on Parallel and Distributed Systems, pp. 244-251, 2012.

C. Wang, N. Cao, J. Li, K. Ren, and W. Lou, “Secure Ranked Keyword Search over Encrypted Cloud Data," Proceedings of IEEE 30th International Conference on Distributed Computing Systems, pp. 253-262, 2012.

K.S. Candan, J.W. Kim, P. Nagarkar, M. Nagendra, and Y. Renwei, "RanKloud: Scalable Multimedia Data Processing in Server Clusters," IEEE MultiMedia, Vol. 18, No. 1, pp. 64-77, 2010. crossref(new window)

C. Doulkeridis and K. Norvag, "On Saying "Enough Already!" in MapReduce," Proceeding of the 1st International Workshop on Cloud Intelligence, 2012.

C. Gentry, "Fully homomorphic encryption using ideal lattices," Proceedings of the Forty-first Annual ACM Symposium on Theory of Computing, pp. 169-178, 2009.

S. Tu, M.F. Kaashoek, S. Madden, and N. Zeldovich, "Processing Analytical Queries over Encrypted data," Proceedings of the Very Large Data Bases Endowment, pp. 289-300, 2013.

T. Ge and S. Zdonik, "Answering Aggregation Queries in a Secure System Model," Proceedings of the International Conference on Very Large Data Bases, pp. 519-530, 2007.

P. Paillier, "Public-key Cryptosystems based on Composite Degree Residuosity Classes," Proceedings of the 17th International Conference on Theory and Application of Cryptographic Techniques, pp. 223-238, 1999.

TPC-H,, 2015. 9. 1

Amazon EC2,, 2015. 9. 1

M. Jang, A. Cho, and J. Chang, "Cache View Based Top-k Query Processing for Encrypted Data Analysis," Lecture Notes in Electrical Engineering, Vol. 330, pp. 725-730, 2015. crossref(new window)

X Liao and J. Li, "Privacy-preserving and Secure Top-k Query in Two-tier Wireless Sensor Network," Proceedings of the IEEE Global Communications Conference, pp. 335-341, 2012.

J. W. Kim "Data Partitioning on MapReduce by Leveraging Data Utility," Journal of Korea Multimedia Society Vol. 16, No. 5, pp. 657-666, 2013. crossref(new window)