Genetic algorithm-based clustering approach for k-anonymization

Expert Systems with Applications

Volumn 36, Issue 6, 2009, Pages 9784-9792

  Lin, Jun Lin ^a   Wei, Meng Cheng ^a  

^a YUAN ZE UNIVERSITY   (Taiwan)

Author keywords

Clustering; Genetic algorithm; k Anonymity

Indexed keywords

CLUSTERING; CLUSTERING APPROACHES; CLUSTERING TECHNIQUES; CROSSOVER OPERATIONS; DATA SETS; INDIVIDUAL IDENTIFICATIONS; INFORMATION LOSS; K-ANONYMITY; K-ANONYMIZATION; MICRODATA; NOVEL GENETIC ALGORITHMS; TRADITIONAL CLUSTERING;

DATA PRIVACY; GENETIC ALGORITHMS;

CLUSTERING ALGORITHMS;

EID: 64049117728     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2009.02.009     Document Type: Article

References (30)

1. Agrawal, R., & Srikant, R. (2000). Privacy-preserving data mining. In Proceedings of the 2000 ACM SIGMOD international conference on management of data.
2. Asuncion, A., & Newman, D. J. (2007). UCI Machine Learning Repository. Irvine, CA: University of California, School of Information and Computer Science. Available from .
3. Babu G.P., and Murty M.N. A near-optimal initial seed value selection in k-means algorithm using a genetic algorithm. Pattern Recognition Letters 14 10 (1993) 763-769
4. Byun, J.-W., Kamra, A., Bertino, E., & Li, N. (2007). Efficient k-anonymization using clustering techniques. In International conference on database systems for advanced applications (DASFAA).
5. Chiu, C.-C., & Tsai, C.-Y. (2007). A k-anonymity clustering method for effective data privacy preservation. In Third international conference on advanced data mining and applications (ADMA).
6. Ciriani V., di Vimercati S.D.C., Foresti S., and Samarati P. K-Anonymity. Security in decentralized data management (2007), Springer-Verlag
7. Cowgill M., Harvey R., and Watson L. A genetic algorithm approach to cluster analysis. Computers and Mathematics with Applications 37 7 (1999) 99-108
8. Fung B.C.M., Wang K., and Yu P.S. Top-down specialization for information and privacy preservation. Proceedings of the 21st IEEE international conference on data engineering (ICDE'05), Washington, DC, USA (2005), IEEE Computer Society 205-216
9. Goldberg D.E. Genetic algorithms in search, optimization and machine learning (1989), Addison-Wesley Longman Publishing Co., Inc., Boston, MA, USA
10. Hall L., Ozyurt I., and Bezdek J. Clustering with a genetically optimized approach. IEEE Transactions on Evolutionary Computation 3 2 (1999) 103-112
11. LeFevre, K., DeWitt, D. J., & Ramakrishnan, R. (2006). Mondrian multidimensional k-anonymity. In Proceedings of the 22nd IEEE international conference on data engineering (ICDE'06).
12. Li, J., Gao, X., & Jiao, L.-C. (2003). A GA-based clustering algorithm for large data sets with mixed and categorical values. In Proceedings of the 5th international conference on computational intelligence and multimedia applications (ICCIMA 2003) (pp. 102-107).
13. Li, N., & Li, T. (2007). t-Closeness: Privacy beyond k-anonymity and l-diversity. In Proceedings of the 23rd IEEE international conference on data engineering (ICDE'07).
14. Lin J.-L., and Cheng Y.-W. Privacy preserving itemset mining through noisy items. Expert Systems with Applications 36 3 (2009) 5711-5717
15. Lin, J.-L., & Wei, M.-C. (2008). An efficient clustering method for k-anonymization. In International workshop on privacy and anonymity in the information society (PAIS).
16. Lin J.-L., Wei M.-C., Li C.-W., and Hsieh K.-C. A hybrid method for k-anonymization. Proceedings of IEEE Asia-Pacific Services Computing Conference (APSCC'08) (2008), IEEE Computer Society, Yilan, Taiwan 385-390
17. Lin H.-J., Yang F.-W., and Kao Y.-T. An efficient GA-based clustering technique. Tamkang Journal of Science and Engineering 8 2 (2005) 113-122
18. Loukides, G., & Shao, J. (2007). Capturing data usefulness and privacy protection in k-anonymisation. In Proceedings of the 2007 ACM symposium on applied computing.
19. Lunacek M., Whitley D., and Ray I. A crossover operator for the k-anonymity problem. GECCO'06: Proceedings of the 8th annual conference on Genetic and evolutionary computation, New York, NY, USA (2006), ACM 1713-1720
20. Machanavajjhala, A., Gehrke, J., Kifer, D., & Venkitasubramaniam, M. (2006). l-Diversity: Privacy beyond k-anonymity. In Proceedings of the 22nd IEEE international conference on data engineering (ICDE'06).
21. Maulik U., and Bandyopadhyay S. Genetic algorithm-based clustering technique. Pattern Recognition 33 9 (2000) 1455-1465
22. Maulik U., and Bandyopadhyay S. Fuzzy partitioning using a real-coded variable-length genetic algorithm for pixel classification. IEEE Transactions on Geoscience and Remote Sensing 41 5 (2003) 1075-1081
23. Omran M.G., Engelbrecht A.P., and Salman A. An overview of clustering methods. Journal Intelligent Data Analysis 11 6 (2007) 583-605
24. Samarati P. Protecting respondent's privacy in microdata release. IEEE Transactions on Knowledge and Data Engineering 13 6 (2001) 1010-1027
25. Scheunders P. A genetic c-means clustering algorithm applied to color image quantization. Pattern Recognition 30 6 (1997) 859-866
26. Solanas, A., Sebé, F., & Domingo-Ferrer, J. (2008). Micro-aggregation-based heuristics for p-sensitive k-anonymity: One step beyond. In International workshop on privacy and anonymity in the information society (PAIS).
27. Sweeney L. K-Anonymity: A model for protecting privacy. International Journal on Uncertainty, Fuzziness and Knowledge-based Systems 10 5 (2002) 557-570
28. Wong, R. C.-W., Li, J., Fu, A. W.-C., & Wang, K. (2006). (α, k)-Anonymity: an enhanced k-anonymity model for privacy preserving data publishing. In Proceedings of the 12th ACM SIGKDD international conference on knowledge discovery and data mining.
29. Wu F.-X. Genetic weighted k-means algorithm for clustering large-scale gene expression data. BMC Bioinformatics 9 Suppl. 6 (2008)
30. Xu R., and Wunsch II D. Survey of clustering algorithms. IEEE Transactions on Neural Networks 16 3 (2005) 645-678