LinkMan:在线安全论坛中超链接驱动的不当行为检测

Risul Islam, Ben Treves, Md Omar Faruk Rokon, M. Faloutsos
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引用次数: 2

摘要

我们如何检测和分析在线论坛中由超链接驱动的不当行为?在线论坛包含大量用户生成的内容,其中的主题和评论经常由超链接补充。这些超链接通常带有恶意,我们将其称为“超链接驱动的不当行为”。我们提出LinkMan,一个系统的功能套件,以检测和分析超链接驱动的不当行为在网上论坛。我们以独特的视角关注用户的超链接分享行为,以发现不当行为。LinkMan可以将这些超链接分类为:a)网络钓鱼,b)垃圾邮件,b)推销恶意产品。我们的方法包括三个高级阶段:(a)从文本数据中提取超链接,(b)识别行为不当的超链接,以及(c)对超链接共享的行为模式建模,其中我们识别关键超链接并分析超链接共享的协作动态。此外,我们将我们的方法作为一个强大且易于使用的开放平台来实现。我们使用LinkMan来发现来自三个在线安全论坛的不当行为,我们希望这些论坛的用户更有安全意识。我们表明,与以前的解决方案相比,我们的方法在检索和分类超链接方面工作得非常好。此外,我们还发现了一些不寻常的、经常是系统性的不当行为:(a)我们发现了总共637个行为不当的超链接,(b)我们在推广超链接方面确定了30个串通的用户组。我们的工作是朝着全面挖掘在线论坛和发现行为不端的用户迈出的重要一步。
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LinkMan: hyperlink-driven misbehavior detection in online security forums
How can we detect and analyze hyperlink-driven misbehavior in online forums? Online forums contain enormous amounts of user-generated content, with threads and comments frequently supplemented by hyperlinks. These hyperlinks are often posted with malicious intention and we refer to this as 'hyperlink-driven misbehavior'. We present LinkMan, a systematic suite of capabilities, to detect and analyze hyperlink-driven misbehavior in online forums. We take a unique perspective focusing on hyperlink sharing practices of the users to spot misbehavior. LinkMan can categorize these hyperlinks as: a) phishing, b) spamming, and b) promoting malicious products. Our approach consists of three high-level phases: (a) extracting hyperlinks from the textual data, (b) identifying misbehaving hyperlinks, and (c) modeling the behavioral patterns of hyperlink sharing, where we identify key hyperlinks and analyze the collaboration dynamics of hyperlink sharing. In addition, we implement our approach as a powerful and easy-to-use open platform for practitioners. We apply LinkMan to spot misbehavior from three online security forums, where we expect the users to be more security-aware. We show that our approach works very well in terms of retrieving and classifying hyperlinks compared to previous solutions. Furthermore, we find non-trivial and often systematic misbehavior: (a) we find a total of 637 misbehaving hyperlinks, and (b) we identify 30 colluding groups of users in terms of promoting hyperlinks. Our work is a significant step towards mining online forums and detecting misbehaving users comprehensively.
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