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首页> 外文会议>2011 IEEE International Conference on Intelligence and Security Informatics >Identifying Dark Web clusters with temporal coherence analysis
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Identifying Dark Web clusters with temporal coherence analysis

机译：通过时间相干分析识别Dark Web集群

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摘要

Extremists are actively utilizing social media as propaganda to promote their ideologies. Online forums are ideal platforms to draw attention from worldwide Internet users to the timely issues and some opinions in these discussions can be threatening the public safety. It is of great interest for the intelligence to identify clusters on these forums and capture the topics of discussions and their development. Previous work in cluster identification focused on social networks constructed by the direct interactions between users utilizing link analysis techniques. However, the direct interactions between users may only capture one potential relationship between forum users. Users who share common interests may not necessarily interact with each other directly. On the other hand, they may be active in similar events simultaneously. In this paper, we propose a temporal coherence analysis approach to identify clusters of users from the Dark Web data. Users are represented as vectors of activeness and clusters are extracted with the support of temporal coherence analysis. We tested our proposed methods on both synthetic dataset and real world dataset. Using the real-world Dark Web dataset, three clusters were identified and each cluster was also associated with a specific theme. It shows that a cluster of users participating in a theme of discussion can be discovered without using any content analysis but only using temporal analysis.
机译：极端主义者正在积极利用社交媒体来宣传他们的意识形态。在线论坛是吸引全球互联网用户关注及时问题的理想平台，这些讨论中的某些观点可能会威胁到公众安全。情报部门非常感兴趣，可以在这些论坛上确定集群并捕获讨论的主题及其发展。集群识别的先前工作重点是由用户之间使用链接分析技术进行直接交互而构建的社交网络。但是，用户之间的直接交互只能捕获论坛用户之间的一种潜在关系。拥有共同利益的用户不一定会直接相互交流。另一方面，它们可能同时在相似事件中处于活动状态。在本文中，我们提出了一种时间相干分析方法，以从Dark Web数据中识别出用户群。用户表示为活动的向量，并在时间相干分析的支持下提取聚类。我们在合成数据集和真实数据集上测试了我们提出的方法。使用真实世界的Dark Web数据集，确定了三个群集，每个群集还与一个特定主题相关联。它表明可以在不使用任何内容分析而仅使用时间分析的情况下发现参与讨论主题的一组用户。

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