Characterizing Activity on the Deep and Dark Web
Characterizing Activity on the Deep and Dark Web
复制标题
表征深网和暗网的活动
DOI：
10.1145/3308560.3316502
复制
发表时间：
2019
期刊：
影响因子：
--
通讯作者：
Kristina Lerman
中科院分区：
文献类型：
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作者：
N. Tavabi;Nathan Bartley;A. Abeliuk;Sandeep Soni;Emilio Ferrara;Kristina Lerman
深网和暗网（d2web）是指访问受限的网站，需要注册，身份验证或更复杂的加密协议才能访问它们。这些网站是各种非法活动的中心：交易毒品、窃取用户凭据、黑客工具，以及协调攻击和操纵活动。尽管d2web对网络犯罪很重要，但它还没有被系统地调查过。在本文中，我们研究了一个大型语料库的消息发布到80 d2web论坛在一年多的时间。我们使用LDA确定讨论的主题，并使用非参数HMM来模拟论坛主题的演变。然后，我们研究讨论的动态模式，并确定具有相似模式的论坛。我们表明，我们的方法表面隐藏的相似性在不同的论坛，可以帮助识别异常事件，在这个丰富的，异构的数据。
The deep and darkweb (d2web) refers to limited access web sites that require registration, authentication, or more complex encryption protocols to access them. These web sites serve as hubs for a variety of illicit activities: to trade drugs, stolen user credentials, hacking tools, and to coordinate attacks and manipulation campaigns. Despite its importance to cyber crime, the d2web has not been systematically investigated. In this paper, we study a large corpus of messages posted to 80 d2web forums over a period of more than a year. We identify topics of discussion using LDA and use a non-parametric HMM to model the evolution of topics across forums. Then, we examine the dynamic patterns of discussion and identify forums with similar patterns. We show that our approach surfaces hidden similarities across different forums and can help identify anomalous events in this rich, heterogeneous data.