1 |
J. L. Lin, M. C. Wei, C. W. Li, and K. C. Hsieh, "A hybrid method for k-anonymization," Asia-Pacific Services Computing Conference, 2008. APSCC'08. IEEE. IEEE, 2008. http://doi.org/10.1109/APSCC.2008.65
DOI
|
2 |
K. Lefevre and D. J. Dewitt, "Mondrian Multidimensional K-Anonymity," Data Engineering, 2006. ICDE'06. Proceedings of the 22nd International Conference on. IEEE, 2006. http://doi.ieeecomputersociety.org/10.1109/ICDE.2006.101
DOI
|
3 |
B. Hore, R. C. Jammalamadaka, and S. Mehrotra, "Flexible Anonymization For Privacy Preserving Data Publishing : A Systematic Search Based Approach," SDM, 2007. http://dx.doi.org/10.1137/1.9781611972771.51
DOI
|
4 |
G. Ghinita, P. Karras, P. Kalnis, and N. Mamoulis, "Fast data anonymization with low information loss," Proceedings of the 33rd international conference on Very large data bases. VLDB Endowment, 2007. Retrieved from http://dl.acm.org/citation.cfm?id=1325938\nhttp://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.138.3217
|
5 |
X. Zhang, C. Liu, S. Nepal, C. Yang, W. Dou, and J. Chen, "A hybrid approach for scalable sub-tree anonymization over big data using MapReduce on cloud," Journal of Computer and System Sciences, vol. 80, no. 5, pp. 1008-1020, 2014. http://doi.org/10.1016/j.jcss.2014.02.007
DOI
|
6 |
M. E. Nergiz and M. Z. Gok, "Hybrid k-Anonymity," Computers & Security, vol. 44, pp. 51-63, 2014. http://doi.org/10.1016/j.cose.2014.03.006
DOI
|
7 |
J. J. Panackal and A. S. Pillai, "Adaptive Utility-based Anonymization Model: Performance Evaluation on Big Data Sets," Procedia Computer Science, vol. 50, pp. 347-352, 2015. http://doi.org/10.1016/j.procs.2015.04.037
DOI
|
8 |
E. T. Wang and G. Lee, "An efficient sanitization algorithm for balancing information privacy and knowledge discovery in association patterns mining," Data & Knowledge Engineering, Jun., vol. 65, no. 3, pp. 463-484, 2008.. http://doi.org/10.1016/j.datak.2007.12.005
DOI
|
9 |
Y. Pan, X. L. Zhu, and T. G. Chen, "Research on privacy preserving on K-anonymity," Journal of Software, vol. 7, no. 7, pp. 1649-1656, 2012. http://doi.org/10.4304/jsw.7.7.1649-1656
|
10 |
M. E. Nergiz, M. Z. Gok, and U. ozkanli, "Preservation of utility through hybrid k-anonymization," in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2013, vol. 8058 LNCS, pp. 97-111. http://doi.org/10.1007/978-3-642-40343-9_9
DOI
|
11 |
S. Moro and R. M. S. Laureano, "Using Data Mining for Bank Direct Marketing: An application of the CRISP-DM methodology," European Simulation and Modelling Conference, 2011. Retrieved from http://archive.ics.uci.edu/ml/datasets/Bank+Marketing
|
12 |
H. A. Elsalamony, "Bank Direct Marketing Analysis of Data Mining Techniques," International Journal of Computer Applications, 2014, pp. 12-22. http://www.ijcaonline.org/archives/volume85/number7/14852-3218
|
13 |
S. Moro, P. Cortez, and P. Rita, "A data-driven approach to predict the success of bank telemarketing," Decision Support Systems, 2014, vol. 62, pp. 22-31. http://doi.org/10.1016/j.dss.2014.03.001
DOI
|
14 |
G. Ateniese, R. Di Pietro, L. V. Mancini, and G. Tsudik, "Scalable and efficient provable data possession," Proceedings of the 4th international conference on Security and privacy in communication netowrks. ACM, 2008. http://doi.org/10.1145/1460877.1460889
DOI
|
15 |
X. Dong, J. Yu, Y. Luo, Y. Chen, G. Xue, and M. Li, "Achieving an effective, scalable and privacy-preserving data sharing service in cloud computing," computers & security, pp. 151-164, 2014. http://doi.org/10.1016/j.cose.2013.12.002
DOI
|
16 |
R. Buyya, C.S. Yeo, S. Venugopal, J. Broberg, and L. Brandic, "Cloud computing and emerging IT platforms: Vision, hype, and reality for delivering computing as the 5th utility," Future Generation computer systems, vol. 25, pp. 599-616, 2009. http://doi.org/10.1016/j.future.2008.12.001
DOI
|
17 |
W. Cohen and D. Levinthal, "Absorptive capacity: a new perspective on learning and innovation," Administrative science quarterly, pp. 128-152, 1990. http://doi.org/10.2307/2393553
DOI
|
18 |
L. Wang, J. Zhan, W. Shi, and Y. Liang, "In cloud, can scientific communities benefit from the economies of scale?" Parallel and Distributed Systems, IEEE Transactions on. 23, no. 2, pp. 296-303, 2012. http://doi.org/10.1109/TPDS.2011.144
DOI
|
19 |
X. Yang, L. Wang, and G. Laszewski, "Recent Research Advances in e-Science," Cluster Computing, 2009, vol. 12, no. 4, pp. 353-356. http://doi.org/10.1007/s10586-009-0104-0
DOI
|
20 |
D. Zissis and D. Lekkas, "Addressing cloud computing security issues," Future Generation computer systems, vol. 28, no. 3, pp. 583-592, 2012. http://doi.org/10.1016/j.future.2010.12.006
DOI
|
21 |
P. Samarati, "Protecting respondents' identities in microdata release," IEEE Transactions on Knowledge and Data Engineering, vol. 13, no. 6, pp. 1010-1027, 2001. http://doi.org/10.1109/69.971193
DOI
|
22 |
R. C. Wong, J. Li, A. W. Fu, and K. Wang, " ( ,k)-Anonymity : An Enhanced k -Anonymity Model for Privacy-Preserving Data Publishing," Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining. ACM, 2006. http://doi.org/10.1145/1150402.1150499
DOI
|
23 |
S. Kumara, S. Singhb, A. Singhc, and J. Alid, "Virtualization, The Great Thing and Issues in Cloud Computing," International journal of Current Engineering and Technology, pp. 338-341, 2013. http://inpressco.com/wp-content/uploads/2013/03/Paper18 338-341.pdf
|
24 |
M. E. Nergiz and C. Clifton, " -presence without complete world knowledge," IEEE Transactions on Knowledge and Data Engineering, 2010, vol. 22, no. 6, pp. 868-883. http://doi.org/10.1109/TKDE.2009.125
DOI
|
25 |
R. J. Bayardo and R. Agrawal, "Data privacy through optimal k-anonymization," Data Engineering, 2005. ICDE 2005. Proceedings. 21st International Conference on. IEEE, 2005. http://doi.org/10.1109/ICDE.2005.42
DOI
|
26 |
M. E. Nergiz, M. Z. Gok, and U. Ozkanli, "Preservation of utility through hybrid k-anonymization," Trust, Privacy, and Security in Digital Business. Springer Berlin Heidelberg, pp. 97-111, 2013. http://doi.org/10.1007/978-3-642-40343-9_9
DOI
|
27 |
C. Kim, "Performance Analysis of Top-K High Utility Pattern Mining Methods," JICS, vol. 16, no. 15, pp. 89-95, 2015. http://dx.doi.org/10.7472/jksii.2015.16.6.89
DOI
|
28 |
K. Lefevre, "Incognito : Efficient Full-Domain K-Anonymity," Proceedings of the 2005 ACM SIGMOD international conference on Management of data. ACM, 2005. http://doi.acm.org/10.1145/1066157.1066164
DOI
|
29 |
A. Machanavajjhala, D. Kifer, J. Gehrke, and M. Venkitasubramaniam, "L-Diversity," ACM Transactions on Knowledge Discovery from Data, vol. 1, no. 1, p. 3-es, 2007. http://doi.org/10.1145/1217299.1217302
DOI
|
30 |
M. E. Nergiz, M. Atzori, and C. Clifton, "Hiding the presence of individuals from shared databases," Proceedings of the 2007 ACM SIGMOD international conference on Management of data. ACM, 2007. http://doi.org/10.1145/1247480.1247554
DOI
|
31 |
M. E. Nergiz and C. Clifton, "Thoughts on k-anonymization," Data & Knowledge Engineering, 2007, vol. 63, no. 3, pp. 622-645. http://doi.org/10.1016/j.datak.2007.03.009
DOI
|
32 |
G. Aggarwal, R. Panigrahy, T. Feder, D. Thomas, K. Kenthapadi, S. Khuller, and A. Zhu, "Achieving anonymity via clustering," Proceedings of the twenty-fifth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems. ACM, 2006. http://doi.org/10.1145/1798596.1798602
DOI
|