论文标题
暗网市场中的自动用户分析：可伸缩性研究
Automatic User Profiling in Darknet Markets: a Scalability Study
论文作者
论文摘要
在这项研究中，我们研究了不同在线域中最先进的用户分析技术的可扩展性。更具体地说，这项工作旨在了解当前计算样式方法方法的可靠性和局限性，当将这些方法应用于地下FORA时，用户群体可能与其他在线平台（主要是男性，年轻年龄和更高的计算机使用）和试图隐藏其身份的网络犯罪者有可能不同。由于没有可用的地面真相，也没有用于验证目的的历史调查的经过验证的犯罪数据，因此我们从Clearweb论坛中收集了新数据，这些数据确实包括用户人口统计数据，并且在用户群体（例如，技术社区）（例如，技术社区）可能与地下FORA更密切相关，而不是常用的社交媒体基准数据集，显示出更均衡的用户人群。
In this study, we investigate the scalability of state-of-the-art user profiling technologies across different online domains. More specifically, this work aims to understand the reliability and limitations of current computational stylometry approaches when these are applied to underground fora in which user populations potentially differ from other online platforms (predominantly male, younger age and greater computer use) and cyber offenders who attempt to hide their identity. Because no ground truth is available and no validated criminal data from historic investigations is available for validation purposes, we have collected new data from clearweb forums that do include user demographics and could be more closely related to underground fora in terms of user population (e.g., tech communities) than commonly used social media benchmark datasets showing a more balanced user population.
