摘要
针对社交网络隐私保护问题,本文提出一种新的隐私保护方法——k-subgraph划分算法,它通过对社交网络进行分割,通过泛化顶点标签和扰乱图的结构特征,来对社交网络进行匿名化处理,拟达到隐私保护的目的。仿真实验表明,该方法可以有效的保护社交网络中个体的隐私信息,同时保证了社交网络中匿名数据的可用性。
In view of the social network privacy protection issues, this paper proposes a new privacy protection method- k- subgraph division rules, it through the social network segmentation, through generalization vertex labels and disrupt the figure structure characteristics, come to anonymize the social network, is proposed to achieve the purpose of privacy protection;Simulation experiments show that this method can offer in a network of individual privacy protection, anonymous social network at the same time also can guarantee availability.
出处
《科技通报》
北大核心
2015年第7期119-121,125,共4页
Bulletin of Science and Technology
基金
河南省科技攻关项目(No.122102210510)
河南省教育厅科技攻关项目(No.13A520786)
关键词
社交网络
隐私保护
泛化
数据发布
信息损失
social network service
privacy protection
generalization
data publication
information loss