Secure and Faster NN Queries on Outsourced Metric Data Assets
 | International Journal of Computer Trends and Technology (IJCTT) |  |
| © - November Issue 2013 by IJCTT Journal | ||
| Volume-5 Issue-6 | ||
| Year of Publication : 2013 | ||
| Authors :Renuka Bandi , Madhu Babu Ch |
Renuka Bandi , Madhu Babu Ch"Secure and Faster NN Queries on Outsourced Metric Data Assets"International Journal of Computer Trends and Technology (IJCTT),V5(6):281-286 November Issue 2013 .ISSN 2231-2803.www.ijcttjournal.org. Published by Seventh Sense Research Group.
Abstract:- -Cloud computing enables outsourcing of data in pay per use fashion. This will help data owners to have services of storage without the need for investment. However, they have security concerns as the cloud service providers focus is on storage instead of security. In this paper we consider a case where three parties are involved. They are cloud server, data owner and trusted client. Data owners outsource their metric data assets to cloud server. The cloud server is provides storage services to people across the world. The data owners can also give access to their data to trusted clients. We proposed techniques to have secure communication among the three parties. The data flown between the data owners and cloud server is protected as the data is transformed and encrypted before string in cloud server. When any client accesses data, it is decrypted automatically and thus there is secure communication among the three parties. We built a prototype application that shows the efficiency of our security mechanisms. The empirical results revealed that the proposed system supports efficient NN queries besides enabling secure communication among the three parties.
References:-
[1] S. Berchtold, D.A. Keim, and H.-P.Kriegel, “The X-Tree : An IndexStructure for High-Dimensional Data,” Proc. 22nd Int’l Conf. VeryLarge Databases, pp. 28-39, 1996.
[2] N. Beckmann, H.-P.Kriegel, R. Schneider, and B. Seeger, “The R*-Tree: An Efficient and Robust Access Method for Points andRectangles,” Proc. ACM SIGMOD Int’l Conf. Management of Data,pp. 322-331, 1990.
[3] E. Cha´vez, G. Navarro, R.A. Baeza-Yates, and J.L. Marroqui´n,“Searching in Metric Spaces,” ACM Computing Surveys, vol. 33,no. 3, pp. 273-321, 2001.
[4] G.R. Hjaltason and H. Samet, “Index-Driven Similarity Search inMetric Spaces,” ACM Trans. Database Systems, vol. 28, no. 4,pp. 517-580, 2003.
[5] P. Ciaccia, M. Patella, and P. Zezula, “M-Tree: An Efficient AccessMethod for Similarity Search in Metric Spaces,” Proc. Very LargeDatabases (VLDB), pp. 426-435, 1997.
[6] T. Bozkaya and Z.M. O ¨ zsoyoglu, “Indexing Large Metric Spacesfor Similarity Search Queries,” ACM Trans. Database Systems,vol. 24, no. 3, pp. 361-404, 1999.
[7] P. Yianilos, “Data Structures and Algorithms for NearestNeighbor Search in General Metric Spaces,” Proc. Fourth Ann.ACM-SIAM Symp.Discrete Algorithms (SODA), pp. 311-321, 1993.
[8] C.T. Jr, A.J.M. Traina, B. Seeger, and C. Faloutsos, “Slim-Trees: High Performance Metric Trees Minimizing Overlap betweenNodes,” Proc. Seventh Int’l Conf. Extending Database Technology(EDBT), pp. 51-65, 2000.
[9] T. Seidl and H.P. Kriegel, “Optimal Multi-Step k-NearestNeighbor Search,” Proc. ACM SIGMOD Int’l Conf. Management ofData, pp. 154-165, 1998.
[10] V. Athitsos, M. Potamias, P. Papapetrou, and G. Kollios, “NearestNeighbor Retrieval Using Distance-Based Hashing,” Proc. IEEE24th Int’l Conf. Data Eng. (ICDE), pp. 327-336, 2008.
[11] A. Gionis, P. Indyk, and R. Motwani, “Similarity Search in HighDimensions via Hashing,” Proc. 25th Int’l Conf. Very LargeDatabases (VLDB), pp. 518-529, 1999.
[12] C. Faloutsos and K.-I. Lin, “FastMap: A Fast Algorithm forIndexing, Data-Mining and Visualization of Traditional andMultimedia Data Sets,” Proc. ACM SIGMOD Int’l Conf. Managementof Data, pp. 163-174, 1995.
[13] H. Hacigu¨mu¨ s, S. Mehrotra, and B.R. Iyer, “Providing Database asa Service,” Proc. 18th Int’l Conf. Data Eng. (ICDE), pp. 29-40, 2002.
[14] H. Hacigu¨mu¨ s, B.R. Iyer, C. Li, and S. Mehrotra, “Executing SQLover Encrypted Data in the Database-Service-Provider Model,”Proc. ACM SIGMOD Int’l Conf. Management of Data, pp. 216-227,2002.
[15] E. Damiani, S.D.C. Vimercati, S. Jajodia, S. Paraboschi, and P.Samarati, “Balancing Confidentiality and Efficiency in UntrustedRelational DBMSs,” Proc. 10th ACM Conf. Computer and Comm.Security (CCS), pp. 93-102, 2003.
[16] R. Agrawal, J. Kiernan, R. Srikant, and Y. Xu, “Order-PreservingEncryption for Numeric Data,” Proc. ACM SIGMOD Int’l Conf.Management of Data, pp. 563-574, 2004.
[17] M.L. Yiu, G. Ghinita, C.S. Jensen, and P. Kalnis, “OutsourcingSearch Services on Private Spatial Data,” Proc. IEEE 25th Int’l Conf.Data Eng. (ICDE), pp. 1140-1143, 2009.
[18] W.K. Wong, D.W. Cheung, B. Kao, and N. Mamoulis, “Secure k-NN Computation on Encrypted Databases,” Proc. 35th ACMSIGMOD Int’l Conf. Management of Data, pp. 139-152, 2009.
[19] L. Sweeney, “k-Anonymity: A Model for Protecting Privacy,” Int’lJ. Uncertainty, Fuzziness and Knowledge-Based Systems, vol. 10, no. 5,pp. 557-570, 2002.
Keywords:-Cloud storage, security, NN queries, metric data, cloud service provider.