收稿日期: 2013-10-15
修回日期: 2013-12-16
网络出版日期: 2014-09-15
基金资助
国家自然科学基金（61272481，61303239）和北京市自然科学基金（4122089）资助
Detection of socialbot networks based on population characteristics
Received date: 2013-10-15
Revised date: 2013-12-16
Online published: 2014-09-15
倪平 , 张玉清 , 闻观行 , 刘奇旭 , 范丹 . 基于群体特征的社交僵尸网络检测方法[J]. 中国科学院大学学报, 2014 , 31(5) : 691 -700 . DOI: 10.7523/j.issn.2095-6134.2014.05.016
An adversary can infiltrate online social networks (OSNs) on a large scale by deploying socialbot network, which is an army of socialbot accounts. This will endanger the information security of online social network and users. To solve the problem, we propose a detection method based on the population characteristics. We extract the following population characteristics: centralized created time, similar screen names, and coincident active time. On the basis of the extracted charateristics and by using date mining method, the method is proposed to detect socialbots networks. The method is used in a data set of 480 000 users of sina microblog and detects many socialbots networks which include 6 899 socialbots accounts. The low false negative rate and false positive rate indicate that the method is feasible and effective.
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