This study addresses the challenges of collecting and analyzing content from Dark Web forums, which are associated with cybercrime, hate, and extremism. Traditional web crawling techniques are inadequate due to the covert nature of the Dark Web. The proposed system employs a novel human-assisted accessibility approach to gain access to Dark Web forums, coupled with URL ordering features for efficient extraction of forum postings. An incremental crawler with a recall-improvement mechanism enhances retrieval and updating of collected content. Experiments demonstrated the effectiveness of these methods, significantly improving access and outperforming standard crawling approaches. The system successfully collected data from over 100 Dark Web forums across three regions, with a case study illustrating the importance of analyzing such content.
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Fu, Tianjun, Ahmed Abbasi, and Hsinchun Chen. "A focused crawler for Dark Web forums." Journal of the American Society for Information Science and Technology 61.6 (2010): 1213-1231.
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