摘要
针对社交网络大量隐私数据保护问题,提出基于有损分解保护隐私数据的策略。通过对数据进行有损分解和特征重构,对数据进行垂直分散存储;利用K匿名算法,对数据进行异构重组,进而实现了对社交网络隐私保护的关联规则数据挖掘。实验结果表明:有损分解隐私数据保护算法,能有效防止数据受到安全性威胁,并且不会造成挖掘准确性的损失。
With a lot of privacy in social network issues of data protection,privacy protection is proposed based on Lossy decomposition data strategy By data Lossy decomposition and characteristics reconstructing,On vertical dispersion data storage;Using K algorithm,and The data are heterogeneous recombination,achieving the privacy protected data mining on social network.Experimental results show Lossy decomposition data privacy protection algorithm,can effectively prevent the data were subjected to a security threat,and will not cause the mining accuracy loss.
出处
《科技通报》
北大核心
2013年第1期128-131,共4页
Bulletin of Science and Technology
基金
2010年度重庆市教委教改项目(103477)
2011年度中国高等教育学会专项课题(2011GZZX013)
关键词
社会网络
隐私保护
有损分解
数据挖掘
social networking services
privacy protection
Lossy decomposition
data mining
