An Integer Linear Programming Scheme to Sanitize Sensitive Frequent Itemsets

Vasileios Kagklis, Vassilios S. Verykios, Giannis Tzimas, A. Tsakalidis
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引用次数: 10

Abstract

In this paper, we propose a novel approach to address the frequent item set hiding problem, by formulating it as an integer linear program (ILP). The solution of the ILP points out the transactions that need to be sanitized in order to achieve the hiding of the sensitive frequent item sets, while the impact on other non-sensitive item sets is minimized. We present a novel heuristic approach to calculate the coefficients of the objective function of the ILP, while at the same time we minimize the side effects introduced by the hiding process. We also propose a sanitization algorithm that performs the hiding on the selected transactions. Finally, we evaluate the proposed method on real datasets and we compare the results of the newly proposed method with those of other state of the art approaches.
敏感频繁项集净化的整数线性规划方法
本文提出了一种解决频繁项集隐藏问题的新方法,将其表述为整数线性规划(ILP)。ILP的解决方案指出了需要消毒的事务,以实现隐藏敏感的频繁项集,同时最小化对其他非敏感项集的影响。我们提出了一种新的启发式方法来计算ILP目标函数的系数,同时我们最小化了隐藏过程引入的副作用。我们还提出了一种对选定的事务执行隐藏的清理算法。最后,我们在真实数据集上评估了所提出的方法,并将新提出的方法的结果与其他最新方法的结果进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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