摘要
提出了一种(p,a)-sensitivek-匿名模型,将敏感属性根据敏感度进行分组,然后给各分组设置不同的约束,并给出了(p,a)-sensitiveK-匿名算法。实验结果表明该方法可以明显地减少隐私泄露,增强了数据发布的安全性。
This paper proposed a novel model (p, a)-sensitive k-anonymity. It divided sensitive attributes into groups according to the sensitivity, and set each group with different restriction. Described the corresponding algorithm to implement the idea. The result of the experiments suggests that the new model is able to reduce privacy disclosure apparently and enforce security of data publishing.
出处
《计算机应用研究》
CSCD
北大核心
2009年第6期2177-2179,2183,共4页
Application Research of Computers
关键词
数据发布
敏感度
K-匿名
隐私泄露
分组
data publishing
sensitivity
k-anonymity
privacy disclosure
group