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An Efficient Top-k Query Processing Algorithm over Encrypted Outsourced-Data in the Cloud
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 Title & Authors
An Efficient Top-k Query Processing Algorithm over Encrypted Outsourced-Data in the Cloud
Kim, Jong Wook; Suh, Young-Kyoon;
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 Abstract
Recently top-k query processing has been extremely important along with the explosion of data produced by a variety of applications. Top-k queries return the best k results ordered by a user-provided monotone scoring function. As cloud computing service has been getting more popular than ever, a hot attention has been paid to cloud-based data outsourcing in which clients` data are stored and managed by the cloud. The cloud-based data outsourcing, though, exposes a critical secuity concern of sensitive data, resulting in the misuse of unauthorized users. Hence it is essential to encrypt sensitive data before outsourcing the data to the cloud. However, there has been little attention to efficient top-k processing on the encrypted cloud data. In this paper we propose a novel top-k processing algorithm that can efficiently process a large amount of encrypted data in the cloud. The main idea of the algorithm is to prune unpromising intermediate results at the early phase without decrypting the encrypted data by leveraging an order-preserving encrypted technique. Experiment results show that the proposed top-k processing algorithm significantly reduces the overhead of client systems from 10X to 10000X.
 Keywords
Cloud Computing;Encryption;Top-k Query;
 Language
Korean
 Cited by
 References
1.
R. Fagin, "Combining Fuzzy Information from Multiple Systems," Proceedings of the 15th ACM SIGACT-SIGMOD- SIGART Symposium on Principles of Database Systems, pp.216-226, 1996.

2.
R. Fagin, A. Lotem, and M. Naor, "Optimal Aggregation Algorithms for Middleware," Proceedings of the 21th ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems, pp.102-113, 2001.

3.
J. W. Kim and K. S. Candna, "Skip-and-prune: Cosine-based Top-k Query Processing for Efficient Context-sensitive Document Retrieval," Proceedings of the 2009 ACM SIGMOD International Conference on Management of Data, pp.115-126, 2009.

4.
S. Tu, M. F. Kaashoek, S. Madden, and N. Zeldovich, "Answering Aggregation Queries in a Secure System Model," Proceedings of the 33th International Conference on Very Large Data Bases, pp.519-530, 2007.

5.
C. Doulkeridis and K. Norvag, "Processing Analytical Queries over Encrypted Data in MapReduce," Proceedings of the VLDB Endowment, pp.289-300, 2013.

6.
W. K. Wongm, B. Kao, D. W. L. Cheung, R. Li, and S. M. Yiu, "Secure Query Processing with Data Interoperability in a Cloud Database Environment," Proceedings of the 40th ACM SIGMOD International Conference on Management of Data, pp.1395-1406, 2014.

7.
C. Gentry, "Fully Homomorphic Encryption Using Ideal Lattices," Proceedings of the 41th Annual ACM Symposium on Theory of Computing, pp.169-178, 2009.

8.
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.

9.
R. Agrawal, J. Kiernan, R. Srikant, and Y. Xu, "Order Preserving Encryption for Numeric Data," Proceedings of the 30th ACM SIGMOD International Conference on Management of Data, pp.563-574, 2004.

10.
A. Boldyreva, N. Chenette, Y. Lee, and A. O'Neill, "Order-preserving Symmetric Encryption," Proceedings of the 28th EUROCRYPT, pp.224-241, 2009.

11.
TPC-H [Internet], http://www.tpc.org/tpch.