摘要
如今微博和Twitter等社交网络平台被广泛地用于交流、创建在线社区并进行社交活动。用户所发布的内容可以被推理出大量隐私信息,这导致社交网络中针对用户的隐私推理技术的兴起。利用用户的文本内容及在线行为等知识可以对用户进行推理攻击,社交关系推理和属性推理是对社交网络用户隐私的两种基本攻击。针对推理攻击保护机制和方法的研究也在日益增加,对隐私推理和保护技术相关的研究和文献进行了分类并总结,最后进行了探讨和展望。
Nowadays, social network platforms such as Weibo and Twitter are widely used to communicate, create online communities, and conduct social activities. The content posted by users can be inferred from a large amount of privacy information, which has led to the rise of privacy inference technology for users in social networks. By using knowledge such as the user’s text content and online behaviors, inference attacks can be performed on users. Social relationship inference and attribute inference are two basic attacks on social network user privacy. The research on the mechanism and method of inference attack protection is also increasing, this paper classifies and summarizes the research and literature related to privacy inference and protection technology. Finally, it discusses and prospects the privacy inference and protection in social networks.
作者
朴杨鹤然
崔晓晖
PIAO Yangheran;CUI Xiaohui(School of Cyber Science and Engineering,Wuhan University,Wuhan 430072,China)
出处
《计算机工程与应用》
CSCD
北大核心
2020年第19期1-12,共12页
Computer Engineering and Applications
基金
国家重点研发计划项目(No.2018YFC1604000)
中央高校基本科研业务费专项基金(No.2042017gf0035)。
关键词
社交网络
推理攻击
隐私保护
机器学习
social networks
inference attacks
privacy protection
machine learning
