A Light in the Dark Web: Linking Dark Web Aliases to Real Internet Identities

Ehsan Arabnezhad, Massimo La Morgia, A. Mei, E. Nemmi, Julinda Stefa
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引用次数: 5

Abstract

Most users have several Internet names. On Face-book or LinkedIn, for example, people usually appear with the real one. On other standard websites, like forums, people often use aliases to protect their real identities with respect to the other users, with no real privacy against the web site and the authorities. Aliases in the Dark Web are different: users expect strong identity protection.In this paper, we show that using both "open" aliases (aliases used in the standard Web) and Dark Web aliases can be dangerous per se. Indeed, we develop tools to link Dark Web to open aliases. For the first time, we perform a massive scale experiment on real scenarios. First between two Dark Web forums, then between the Dark Web forums and the standard forums. Due to a large number of possible pairs, we first reduce the search space cutting down the number of potential matches to a small set of candidates, and then on the selection of the correct alias among these candidates. We show that our methodology has excellent precision, from 87% to 94%, and recall around 80%.
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暗网之光:将暗网别名与真实互联网身份联系起来
大多数用户都有好几个互联网名称。例如,在facebook或LinkedIn上,人们通常与真人一起出现。在论坛等其他标准网站上,人们经常使用别名来保护他们的真实身份,而不是其他用户,对网站和当局没有真正的隐私。暗网中的别名是不同的:用户期望强大的身份保护。在本文中,我们展示了使用“开放”别名(标准Web中使用的别名)和暗网别名本身可能是危险的。事实上,我们开发了将暗网与开放别名连接起来的工具。这是我们第一次在真实场景中进行大规模实验。先是在两个暗网论坛之间,然后在暗网论坛和标准论坛之间。由于存在大量可能的配对,我们首先缩小搜索空间,将潜在匹配的数量减少到一小部分候选对象,然后在这些候选对象中选择正确的别名。我们表明,我们的方法具有优异的精度,从87%到94%,召回率约为80%。
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