Visible to the public Understanding Dark Web: A Systematic Literature Review

TitleUnderstanding Dark Web: A Systematic Literature Review
Publication TypeConference Paper
Year of Publication2022
AuthorsAbdellatif, Tamer Mohamed, Said, Raed A., Ghazal, Taher M.
Conference Name2022 International Conference on Cyber Resilience (ICCR)
Date Publishedoct
KeywordsBibliographies, dark web, Human Behavior, human factors, Measurement, pubcrawl, social networking (online), systematic literature review, Systematics, Terrorism, Web 2.0
Abstract

Web evolution and Web 2.0 social media tools facilitate communication and support the online economy. On the other hand, these tools are actively used by extremist, terrorist and criminal groups. These malicious groups use these new communication channels, such as forums, blogs and social networks, to spread their ideologies, recruit new members, market their malicious goods and raise their funds. They rely on anonymous communication methods that are provided by the new Web. This malicious part of the web is called the "dark web". Dark web analysis became an active research area in the last few decades, and multiple research studies were conducted in order to understand our enemy and plan for counteract. We have conducted a systematic literature review to identify the state-of-art and open research areas in dark web analysis. We have filtered the available research papers in order to obtain the most relevant work. This filtration yielded 28 studies out of 370. Our systematic review is based on four main factors: the research trends used to analyze dark web, the employed analysis techniques, the analyzed artifacts, and the accuracy and confidence of the available work. Our review results have shown that most of the dark web research relies on content analysis. Also, the results have shown that forum threads are the most analyzed artifacts. Also, the most significant observation is the lack of applying any accuracy metrics or validation techniques by most of the relevant studies. As a result, researchers are advised to consider using acceptance metrics and validation techniques in their future work in order to guarantee the confidence of their study results. In addition, our review has identified some open research areas in dark web analysis which can be considered for future research work.

DOI10.1109/ICCR56254.2022.9995741
Citation Keyabdellatif_understanding_2022