Sensitive association rules hiding using electromagnetic field optimization algorithm
作者：
Highlights：
• The proposed method hides sensitive rules using electromagnetic field optimization.
• Several sensitive association rules are hided simultaneously in the method.
• The proposed method also has fewer lost rules than other well-known algorithms.
• Two fitness functions are proposed to find the solution with minimum side effects.
• The method is evaluated on both real-world and synthetic datasets.
摘要
•The proposed method hides sensitive rules using electromagnetic field optimization.•Several sensitive association rules are hided simultaneously in the method.•The proposed method also has fewer lost rules than other well-known algorithms.•Two fitness functions are proposed to find the solution with minimum side effects.•The method is evaluated on both real-world and synthetic datasets.
论文关键词：Privacy preserving data mining,Association rules hiding,Data distortion technique,Electromagnetic field optimization algorithm
论文评审过程：Received 6 November 2017, Revised 13 July 2018, Accepted 14 July 2018, Available online 17 July 2018, Version of Record 31 July 2018.
论文官网地址：https://doi.org/10.1016/j.eswa.2018.07.031
