论文标题
使用作者身份验证折衷的帐户检测：一种新颖的方法
Compromised account detection using authorship verification: a novel approach
论文作者
论文摘要
妥协的合法帐户是将恶意内容传播到在线社交网络（OSN）中的大型用户基础的一种方式。由于这些帐户对用户以及OSN上其他用户造成了很大的损害，因此早期检测非常重要。本文提出了一种基于作者身份验证的新方法，以识别受损的Twitter帐户。由于该方法仅使用从上一个用户的帖子中提取的功能，因此有助于尽早检测以控制损坏。结果，可以以令人满意的精度检测到没有用户配置文件的恶意消息。实验是使用Twitter上折衷帐户的现实世界数据集构建的。结果表明该模型适用于由于达到89％的准确性，因此适用于检测。
Compromising legitimate accounts is a way of disseminating malicious content to a large user base in Online Social Networks (OSNs). Since the accounts cause lots of damages to the user and consequently to other users on OSNs, early detection is very important. This paper proposes a novel approach based on authorship verification to identify compromised twitter accounts. As the approach only uses the features extracted from the last user's post, it helps to early detection to control the damage. As a result, the malicious message without a user profile can be detected with satisfying accuracy. Experiments were constructed using a real-world dataset of compromised accounts on Twitter. The result showed that the model is suitable for detection due to achieving an accuracy of 89%.
