BRBA: A Blocking-Based Association Rule Hiding Method

被引：0

作者：

Cheng, Peng ^{[1
,2
]}

Lee, Ivan ^{[3
]}

Li, Li ^{[1
]}

Tseng, Kuo-Kun ^{[2
]}

Pan, Jeng-Shyang ^{[2
]}

机构：

[1] Southwest Univ, Sch Comp & Informat Sci, Chongqing, Peoples R China

[2] Harbin Inst Technol, Shenzhen Grad Sch, Harbin, Heilongjiang, Peoples R China

[3] Univ South Australia, Sch Informat Technol & Math Sci, Adelaide, SA, Australia

来源：

THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE | 2016年

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Privacy preserving in association rule mining is an important research topic in the database security field. This paper has proposed a blocking-based method to solve the association rule hiding problem for data sharing. It aims at reducing undesirable side effects and increasing desirable side effects, while ensuring to conceal all sensitive rules. The candidate transactions are selected for sanitization based on their relations with border rules. Comparative experiments on real datasets demonstrate that the proposed method can achieve its goals.

引用

页码：4200 / 4201

页数：2

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