摘要
随着互联网的广泛应用,社交网络已成为当今社会信息发布和传播共享的重要载体。然而,社交网络中频繁的数据共享会导致用户的隐私泄露。提出一种基于用户社交网络图的结构和用户节点的特征来披露用户敏感信息的去匿名方法。利用社交网络图的结构特征与节点属性的特征之间的相似性差异实现节点间的映射,从而成功实现匿名数据集的用户去匿名化。在两个数据集的实验证明,该去匿名方法有较好的准确率和运行时间。
With the wide usage of Internet, social network has become an important carrier of information publishing and transmission in contemporary society. However, the anonymized information can still be de-anonymized because of the high frequency da- ta- sharing in social network, which causes the leakage of users＇ privacy information. Proposes a novel de- anonymization method based on the structure of the social network graph of users and the characteristics of user nodes to disclose users~ pri- vate information. It utilizes the similarity difference between the structural features of the social network graph and the char- acteristics of the node attributes to realize the mapping between nodes, so as to successfully de-anonymize the users of anony- mous datasets. Experiments on two real datasets show that our anonymization method outperforms in accuracy and execution time.
出处
《现代计算机》
2018年第3期14-20,共7页
Modern Computer
基金
浙江省科技计划项目(No.2017C01064
No.2017C01055
No.2018C01088)
关键词
社交网络
隐私
相似性
去匿名
Social Network
Privacy
Similarity
De-Anonymization
