URLytics: Profiling Forum Users from their Posted URLs

Ben Treves, Md Rayhanul Masud, M. Faloutsos
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Abstract

Online forums contain a substantial amount of data, but very few studies have focused on mining the URLs posted by users. How can we fully leverage these posted URLs to extract as much information as possible about forum users? We perform a systematic study for extracting as much information as possible about forum users via their URL posting behavior. Within this study we develop a series of tools to analyze the data. Given a forum, we extract the following information: (a) basic statistics and a profile of the forum, (b) a profile for each user based on their referral to accounts in other platforms, (c) identification of communities within the forum, and (d) detection of malicious behavior. Most prior works focus on analyzing the text found in user posts rather than on URLs themselves, as we do here. In our study, we analyze three online security forums and find interesting results: (a) we identify 7% of the users posting social media links on other platforms, (b) we detect 148 groups of users that engage in communities on external social media platforms, (c) we expose 139 malicious users that collectively posted 328 malicious URLs. Additionally, we identify 17 groups with membership spanning across multiple forums, and discover numerous other groups that engage in coordinated malicious behavior. Our work is a significant step towards an all-encompassing system for profiling forum users at large.
URLytics:分析论坛用户发布的url
在线论坛包含大量的数据,但很少有研究关注于挖掘用户发布的url。我们如何充分利用这些张贴的url来提取尽可能多的关于论坛用户的信息?我们进行了一个系统的研究,通过论坛用户的URL发帖行为来提取尽可能多的信息。在这项研究中,我们开发了一系列工具来分析数据。给定一个论坛,我们提取以下信息:(a)论坛的基本统计数据和简介,(b)每个用户基于他们在其他平台上的账户的简介,(c)论坛内社区的识别,以及(d)恶意行为的检测。大多数先前的工作集中于分析用户帖子中的文本,而不是url本身,就像我们在这里所做的那样。在我们的研究中,我们分析了三个在线安全论坛,并发现了有趣的结果:(a)我们确定了7%的用户在其他平台上发布社交媒体链接,(b)我们检测了148组参与外部社交媒体平台社区的用户,(c)我们揭露了139个恶意用户,这些用户总共发布了328个恶意url。此外,我们确定了17个成员跨越多个论坛的组织,并发现了许多其他参与协调恶意行为的组织。我们的工作是朝着全面分析论坛用户的系统迈出的重要一步。
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