论文标题
陷入黑社会:关于Darknet出现的调查
Plunge into the Underworld: A Survey on Emergence of Darknet
论文作者
论文摘要
在网络空间中进行犯罪活动的复杂技术和方法的可用性是一个相关的社会问题。 DarkNet是一种使用Internet基础架构的加密网络技术,只能使用特殊的网络配置和软件工具访问其内容,以访问其内容,而该内容未由搜索引擎索引。多年来,Darknets传统上被用于犯罪活动,并以促进网络犯罪,非法毒品的采购,武器交易和加密货币市场而闻名。在具有压迫性政权的国家,对数字通信的审查制度以及严格的政策促使记者和自由战士匿名使用Darknet技术寻求自由,而其他人则只是将其用于非法活动。最近,麻省理工学院的林肯人工智能实验室增加了一种工具,该工具可用于揭露Darknet背后的非法活动。我们研究了相关的文献综述,以帮助研究人员更好地了解Darknet技术,确定DarkNet的未来研究领域,并最终优化如何利用数据驱动的见解来支持政府机构,以揭示Darknet技术的深度。本文着重于将互联网用于犯罪,tor-services的姓名,Darknet是一条新的数字街道,用于非法药物,研究问题和假设,以指导研究人员在进一步的研究中。最后,在这项研究中,我们提出了一个模型来检查和调查匿名在线非法市场。
The availability of sophisticated technologies and methods of perpetrating criminogenic activities in the cyberspace is a pertinent societal problem. Darknet is an encrypted network technology that uses the internet infrastructure and can only be accessed using special network configuration and software tools to access its contents which are not indexed by search engines. Over the years darknets traditionally are used for criminogenic activities and famously acclaimed to promote cybercrime, procurements of illegal drugs, arms deals, and cryptocurrency markets. In countries with oppressive regimes, censorship of digital communications, and strict policies prompted journalists and freedom fighters to seek freedom using darknet technologies anonymously while others simply exploit it for illegal activities. Recently, MIT's Lincoln Laboratory of Artificial Intelligence augmented a tool that can be used to expose illegal activities behind the darknet. We studied relevant literature reviews to help researchers to better understand the darknet technologies, identify future areas of research on the darknet and ultimately to optimize how data-driven insights can be utilized to support governmental agencies in unraveling the depths of darknet technologies. This paper focuses on the use of the internet for crimes, deanonymization of TOR-services, darknet a new digital street for illicit drugs, research questions and hypothesis to guide researchers in further studies. Finally, in this study, we propose a model to examine and investigate anonymous online illicit markets.