References

Chhinkaniwala, H. and S. Garg, 2014. Privacy gain based multi-iterative k-anonymization to protect respondents privacy. Int. J. Comput., 3: 85-92.
Direct Link  |  

Cormode, G., L. Golab, K. Flip, A. McGregor and D. Srivastava et al., 2009. Estimating the confidence of conditional functional dependencies. Proceedings of the 2009 ACM SIGMOD International Conference on Management of Data, June 29-July 02, 2009, ACM, New York, USA., ISBN: 978-1-60558-551-2, pp: 469-482.

Fung, B.C.M., K. Wang, R. Chen and P.S. Yu, 2010. Privacy-preserving data publishing: A survey of recent developments. ACM Comput. Surv., Vol. 42. 10.1145/1749603.1749605

Hoang, A.T., M.T. Tran, A.D. Duong and I. Echizen, 2012. An indexed bottom-up approach for publishing anonymized data. Proceedings of the 2012 Eighth International Conference on Computational Intelligence and Security (CIS), November 17-18, 2012, IEEE, Guangzhou, China, ISBN: 978-1-4673-4725-9, pp: 641-645.

Jin, X., M. Zhang, N. Zhang and G. Das, 2010. Versatile publishing for privacy preservation. Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, July 25-28, 2010, ACM, New York, USA., ISBN: 978-1-4503-0055-1, pp: 353-362.

Kifer, D., 2009. Attacks on privacy and deFinetti's theorem. Proceedings of the 2009 ACM SIGMOD International Conference on Management of Data, June 29-July 02, 2009, ACM, New York, USA., ISBN: 978-1-60558-551-2, pp: 127-138.

Loukides, G. and J.H. Shao, 2008. An efficient clustering algorithm for k-anonymisation. J. Comput. Sci. Technol., 23: 188-202.
CrossRef  |  Direct Link  |  

Martin, D.J., D. Kifer, A. Machanavajjhala, J. Gehrke and J.Y. Halpern, 2007. Worst-case background knowledge for privacy-preserving data publishing. Proceedings of the IEEE 23rd International Conference on Data Engineering ICDE 2007, April 15-20, 2007, IEEE, Istanbul, Turkey, ISBN: 1-4244-0802-4, pp: 126-135.

Medina, R. and L. Nourine, 2009. A Unified Hierarchy for Functional Dependencies, Conditional Functional Dependencies and Association Rules. In: Formal Concept Analysis. Ferre, S. and S. Rudolph (Eds.). Springer Berlin Heidelberg, Berlin, Germany, pp: 98-113.

Nergiz, M., M. Atzori and C. Clifton, 2007. Hiding the presence of individuals from shared databases. Proceedings of the ACM SIGMOD International Conference on Management of Data, June 12-14, 2007, Beijing, China, pp: 665-676.

Rastogi, V., D. Suciu and S. Hong, 2007. The boundary between privacy and utility in data publishing. Proceedings of the 33rd International Conference on Very Large Data Bases, September 23-28, 2007, VLDB Endowment, Austria, ISBN: 978-1-59593-649-3, pp: 531-542.

Wang, H. and R. Liu, 2011. Privacy-preserving publishing microdata with full functional dependencies. Data Knowl. Eng., 70: 249-268.
CrossRef  |  Direct Link  |  

Wang, P. and J. Wang, 2013. L-diversity algorithm for incremental data release. Appl. Math. Inf. Sci., 7: 2055-2060.
Direct Link  |  

Wong, R.C.W., J. Li, A.W.C. Fu and K. Wang, 2006. The (α, 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, August 20-23, 2006, ACM, New York, USA., ISBN:1-59593-339-5, pp: 754-759.

Xiao, X., Y. Tao and N. Koudas, 2010. Transparent anonymization: Thwarting adversaries who know the algorithm. ACM. Trans. Database Syst., 35: 1-48.
CrossRef  |  Direct Link  |