This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Agarwal, R., and Srikant, R. 2000. Privacy-preserving data mining. In Proceedings. of the ACM SIGMOD Conference on Management of Data, ACM Press, 439–450
Claerhout, B., and DeMoor, G.J.E. 2005. Privacy protection for clinical and genomic data: The use of privacy-enhancing techniques in medicine. International Journal of Medical Informatics, 74(2–4): 257–265
Clifton, C. 2000. Using sample size to limit exposure to data mining. Journal of Computer Security 8(4): 281–307
Clifton, C., and Marks, D. 1996. Security and privacy implications of data mining. In Workshop on Data Mining and Knowledge Discovery, 15–19, Montreal, Canada
Clifton, C., and Thuraisingham, B. 2001. Emerging standards for data mining. Computer Standards & Interfaces, 23(3): 187–193
Da Silva, J.C., Giannella, C., Bhargava, R., Kargupta, H., and Klusch, M. 2005. Distributed data mining and agents, Engineering Applications of Artificial Intelligence, 18(7): 791–807
Du, W., and Zhan, Z. 2002. Building decision tree classifier on private data. In Clifton, C., Estivill-Castro, V. (Eds.), IEEE ICDM Workshop on Privacy, Security and Data Mining, Conferences in Research and Practice in Information Technology, 14, 1–8, Maebashi City, Japan, ACS
Evfimievski, A., Srikant, R., Agrawal, R., and Gehrke, J. 2004. Privacy preserving mining of association rules, Information Systems, 29(4): 343–364
Johnsten, T., and Raghavan, V.V. 2002. A methodology for hiding knowledge in databases. In Clifton, C., Estivill-Castro, C. (Eds.), IEEE ICDM Workshop on Privacy, Security and Data Mining, Conferences in Research and Practice in Information Technology, 14, 9–17, Maebashi City, Japan, ACS
Kargupta, H., Kun, L., Datta, S., Ryan, J., and Sivakumar, K. 2003. Homeland security and privacy sensitive data mining from multi-party distributed resources, Proceedings 12th IEEE International Conference on Fuzzy Systems, FUZZ ’03, 2: 1257–1260
Lindell, Y., and Pinkas, B. 2000. Privacy preserving data mining. In Lecture Notes in Computer Science, 1880: 36–54
Merugu, S., and Ghosh, J. 2005. A privacy-sensitive approach to distributed clustering, Pattern Recognition Letters, 26(4): 399–410
Park, B., and Kargupta, H. 2003. Distributed data mining: algorithms, systems, and applications. In Ye, N. (Ed.), The Handbook of Data Mining, Lawrence Erlbaum Associates, 341–358
Pedrycz, W. 2005. Knowledge-Based Clustering: From Data to Information Granules, John Wiley, Hoboken, NJ
Pedrycz, W. 2002. Collaborative fuzzy clustering, Pattern Recognition Letters, 23(14): 1675–1686
Pinkas, B. 2002. Cryptographic techniques for privacy-preserving data mining. ACM SIGKDD Explorations Newsletter, 4(2): 12–19
Strehl, A., and Ghosh, J. 2002. Cluster ensembles—a knowledge reuse framework for combining multiple partitions. Journal of Machine Learning Research, 3: 583–617
Tsoumakas, G., Angelis, L., and Vlahavas, I. 2004. Clustering classifiers for knowledge discovery from physically distributed databases, Data & Knowledge Engineering, 49(3): 223–242
Verykios, V.S., Bertino, E., Fovino, I.N., Provenza, L.P., Saygin, Y., and Theodoridis, Y. 2004. State-of-the-art in privacy preserving data mining. SIGMOD Record, 33(1): 50–57
Wang, S.L., and Jafari, A. 2005. Using unknowns for hiding sensitive predictive association rules. Proceedings 2005 IEEE International Conference on Information Reuse and Integration, 223–228
Wang, E.T., Lee, G., and Lin, Y.T. 2005. A novel method for protecting sensitive knowledge in association rules mining, Proceedings of the 29th Annual International Computer Software and Applications Conference (COMPSAC 2005), 2: 511–516
Wang, K., Yu, P.S., and Chakraborty, S. 2004. Bottom-up generalization: a data mining solution to privacy protection, Proceedings of the 4th IEEE International Conference on Data Mining, ICDM 2004, 249–256
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2007 Springer Science+Business Media, LLC
About this chapter
Cite this chapter
Cios, K.J., Swiniarski, R.W., Pedrycz, W., Kurgan, L.A. (2007). Data Security, Privacy and Data Mining. In: Data Mining. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-36795-8_16
Download citation
DOI: https://doi.org/10.1007/978-0-387-36795-8_16
Publisher Name: Springer, Boston, MA
Print ISBN: 978-0-387-33333-5
Online ISBN: 978-0-387-36795-8
eBook Packages: Computer ScienceComputer Science (R0)