计算机科学 ›› 2019, Vol. 46 ›› Issue (6): 143-147.doi: 10.11896/j.issn.1002-137X.2019.06.021
吕志泉1, 李昊2, 张宗福2, 张敏2
LV Zhi-quan1, LI Hao2, ZHANG Zong-fu2, ZHANG Min2
摘要: 近年来,社交网络已成为人们日常生活的一部分。社交网络在为人们的社交活动带来便利的同时,也对个人隐私造成了威胁。通常情况下,人们都希望对自身的部分私密社交活动信息进行保护,以阻止亲属、朋友、同事或其他特定群体的访问。较为常见的一种保护措施是以匿名方式进行社交。一些社交网络会为用户提供匿名机制,允许用户以匿名的形式进行部分社交活动,从而将这部分社交活动与主账号分隔开,以达到隐私保护的目的。此外,用户也可以创建额外的账号(小号),并将该账号的属性、朋友关系与主账号进行区别。针对这些保护措施,文中提出了一种基于主题模型的社交网络匿名用户重识别方法。该方法将用户匿名方式(或小号)和非匿名方式(主账号)发布的文本内容进行主题挖掘,并在主题模型的基础上引入时间因素和文本长度因素来构建用户画像,最后通过分析匿名(小号)和非匿名(主账号)用户画像之间的相似度来实现用户身份的重识别。在真实社交网络数据集上的实验表明,该方法能够有效地对社交网络匿名用户或“小号”用户实施身份重识别攻击。
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