Recent Advances in Preserving Privacy Data Mining

Abstract:

A number of privacy preserving techniques have been proposed recently in data mining. In this paper, we provide a review of the state-of-the-art methods for privacy preserving data mining. and discuss methods for randomization, secure multipart computation, and so on. We also make a classification for the privacy preserving data mining technologies, and analyze some works in this field, such as data distortion method for achieving privacy preserving association rule mining. Detailed evaluation criteria of privacy preserving algorithm were illustrated, which include algorithm performance, data utility, and privacy protection degree. Finally, the development of privacy preserving data mining for further directions is given.

• Periodical: Advanced Materials Research (Volumes 798-799)
• Pages: 541-544
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.798-799.541
• Online since: September 2013
• Authors: Gao Ming Yang, Jing Zhao Li, Shun Xiang Zhang
• Keywords: Data Mining (DM), Perturbation, Privacy Preserving, Secure Multipart Computation

References

[1] Benjamin C. M. Fung, Ke Wang, Rui Chen, Philip S. Yu, Privacy-preserving data publishing: A survey of recent developments, ACM Computing Surveys (CSUR), 2010, 1-53.

DOI: 10.1145/1749603.1749605

[2] Rakesh Agrawal, Ramakrishnan Srikant, Privacy-preserving data mining, Proceedings of the 2000 ACM SIGMOD international conference on Management of data, 2000, 439-450.

DOI: 10.1145/335191.335438

[3] J. Vaidya, M. Kantarcıoğlu, C. Clifton, Privacy-preserving naive bayes classification, The VLDB Journal, 2008, 879-898.

DOI: 10.1007/s00778-006-0041-y

[4] S. Gambs, B. Kégl, E. Aïmeur, Privacy-preserving boosting, Data Mining and Knowledge Discovery, 2007, 131-170.

DOI: 10.1007/s10618-006-0051-9

[5] A. Evfimievski, R. Srikant, R. Agrawal, J. Gehrke, Privacy preserving mining of association rules, Information Systems, 2004, 343-364.

DOI: 10.1016/j.is.2003.09.001

[6] Mohammed Golam Kaosar, Russell Paulet, Xun Yi, Fully homomorphic encryption based two-party association rule mining, Data & Knowledge Engineering, 2012, 1-15.

DOI: 10.1016/j.datak.2012.03.003

[7] Vassilios S. Verykios, Elisa Bertino, Igor Nai Fovino, Loredana Parasiliti Provenza, Yucel Saygin, Yannis Theodoridis, State-of-the-art in privacy preserving data mining, ACM SIGMOD Record, 2004, 50-57.

DOI: 10.1145/974121.974131

[8] E. Dasseni, V. Verykios, A. Elmagarmid, E. Bertino, Hiding association rules by using confidence and support, Information Hiding, 2001, 369-383.

DOI: 10.1007/3-540-45496-9_27

[9] S. R. M. Oliveira, O. R. Zaiane, Algorithms for balancing privacy and knowledge discovery in association rule mining, Proceedings of Seventh International Database Engineering and Applications Symposium, 2003., 2003, 54-63.

DOI: 10.1109/ideas.2003.1214911

[10] S. R. M. Oliveira, O. R. Zaiane, Privacy preserving clustering by data transformation, Proc. of the 18th Brazilian Symposium on Databases, 2003, 304-318.

[11] S. R. M. Oliveira, O. R. Zaiane, Privacy-preserving clustering by object similarity-based representation and dimensionality reduction transformation, Proc. of the Workshop on Privacy and Security Aspects of Data Mining (PSADM'04) in conjunction with the Fourth IEEE International Conference on Data Mining (ICDM'04), 2004, 21-30.

DOI: 10.1109/icdm.2004.10081

[12] J. Vaidya, C. Clifton, Privacy preserving association rule mining in vertically partitioned data, Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining, 2002, 639-644.

DOI: 10.1145/775047.775142

[13] M. Kantarcioglu, C. Clifton, Privacy-preserving distributed mining of association rules on horizontally partitioned data, Knowledge and Data Engineering, IEEE Transactions on, 2004, 1026-1037.

DOI: 10.1109/tkde.2004.45

[14] M. Kantarcioglu, R. Nix, J. Vaidya, An efficient approximate protocol for privacy-preserving association rule mining, Advances in Knowledge Discovery and Data Mining, 2009, 515-524.

DOI: 10.1007/978-3-642-01307-2_48

[15] C. E. Shannon, A mathematical theory of communication, ACM SIGMOBILE Mobile Computing and Communications Review, 2001, 3-55.