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The Scientific World Journal
Volume 2014, Article ID 804629, 12 pages
http://dx.doi.org/10.1155/2014/804629
Research Article

A GA-Based Approach to Hide Sensitive High Utility Itemsets

1Innovative Information Industry Research Center, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen 518055, China
2Shenzhen Key Laboratory of Internet Information Collaboration, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen 518055, China
3Department of Computer Science and Information Engineering, National University of Kaohsiung, Kaohsiung 811, Taiwan
4Department of Computer Science and Engineering, National Sun Yat-sen University, Kaohsiung 804, Taiwan
5Department of Mathematics and Computer Sciences, Fuqing Branch of Fujian Normal University, Fuzhou, Fujian 350300, China

Received 29 August 2013; Accepted 11 December 2013; Published 3 March 2014

Academic Editors: J. Shu and F. Yu

Copyright © 2014 Chun-Wei Lin et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Citations to this Article [8 citations]

The following is the list of published articles that have cited the current article.

  • Jerry Chun-Wei Lin, Tsu-Yang Wu, Philippe Fournier-Viger, Guo Lin, Tzung-Pei Hong, and Jeng-Shyang Pan, “A sanitization approach of privacy preserving utility mining,” Advances in Intelligent Systems and Computing, vol. 388, pp. 47–57, 2015. View at Publisher · View at Google Scholar
  • Rishi Soni, Sugandha Rathi, and Virendra Singh Kushwah, “A new algorithm for privacy preservation in utility mining using genetic algorithm,” ACM International Conference Proceeding Series, vol. 04-05-, 2016. View at Publisher · View at Google Scholar
  • Jerry Chun-Wei Lin, Tsu-Yang Wu, Philippe Fournier-Viger, Justin Zhan, Guo Lin, and Miroslav Voznak, “Fast algorithms for hiding sensitive high-utility itemsets in privacy-preserving utility mining,” Engineering Applications of Artificial Intelligence, vol. 55, pp. 269–284, 2016. View at Publisher · View at Google Scholar
  • Rishi Soni, and Sugandha Rathi, “Privacy preservation in utility mining based on genetic algorithm: A new approach,” Advances in Intelligent Systems and Computing, vol. 437, pp. 71–80, 2016. View at Publisher · View at Google Scholar
  • Akbar Telikani, and Asadollah Shahbahrami, “Optimizing association rule hiding using combination of border and heuristic approaches,” Applied Intelligence, 2017. View at Publisher · View at Google Scholar
  • Jerry Chun-Wei Lin, Tzung-Pei Hong, Philippe Fournier-Viger, Jia-Wei Wong, Qiankun Liu, and Justin Zhan, “Efficient hiding of confidential high-utility itemsets with minimal side effects,” Journal of Experimental and Theoretical Artificial Intelligence, vol. 29, no. 6, pp. 1225–1245, 2017. View at Publisher · View at Google Scholar
  • Akbar Telikani, and Asadollah Shahbahrami, “Data Sanitization in Association Rule Mining: An Analytical Review,” Expert Systems with Applications, 2017. View at Publisher · View at Google Scholar
  • Gayathiri, and Poorna, “Effective gene patterned association rule hiding algorithm for privacy preserving data mining on transactional database,” Cybernetics and Information Technologies, vol. 17, no. 3, pp. 92–108, 2017. View at Publisher · View at Google Scholar