A metaheuristic algorithm for hiding sensitive itemsets

Lin, Jerry Chun-Wei and Zhang, Yuyu and Fournier-Viger, Philippe and Djenouri, Youcef and Zhang, Ji ORCID: https://orcid.org/0000-0001-7167-6970 (2018) A metaheuristic algorithm for hiding sensitive itemsets. In: 29th International Conference on Database and Expert Systems Applications (DEXA 2018), 3-6 Sept 2018, Regensburg, Germany.


In this paper, we first present a multi-objective algorithm for hiding the sensitive information with transaction deletion based on the NSGAII framework. The proposed can efficiently sort the non-dominated solutions and find the set of Pareto results for later process. Experimental results on two real datasets illustrated that the proposed algorithm can achieve satisfactory results with fewer side effects compared to the previous single-objective evolutionary approaches.

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Item Type: Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed: Yes
Item Status: Live Archive
Additional Information: Permanent restricted access to Published version in accordance with the copyright policy of the publisher.
Faculty/School / Institute/Centre: Historic - Faculty of Health, Engineering and Sciences - School of Agricultural, Computational and Environmental Sciences (1 Jul 2013 - 5 Sep 2019)
Faculty/School / Institute/Centre: Historic - Institute for Resilient Regions - Centre for Health, Informatics and Economic Research (1 Aug 2018 - 31 Mar 2020)
Date Deposited: 22 May 2020 05:41
Last Modified: 19 Dec 2021 22:31
Uncontrolled Keywords: PPDM, sanitization, evolutionary computation, Pareto solutions
Fields of Research (2008): 08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080109 Pattern Recognition and Data Mining
Fields of Research (2020): 46 INFORMATION AND COMPUTING SCIENCES > 4699 Other information and computing sciences > 469999 Other information and computing sciences not elsewhere classified
Identification Number or DOI: https://doi.org/10.1007/978-3-319-98812-2_45
URI: http://eprints.usq.edu.au/id/eprint/38115

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