June 19, 2021

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Darknet Data Mining — A Canadian Cyber-crime Perspective. (arXiv:2105.13957v1 [cs.CR])

Exploring the darknet can be a daunting task; this paper explores the
application of data mining the darknet within a Canadian cybercrime
perspective. Measuring activity through marketplace analysis and vendor
attribution has proven difficult in the past. Observing different aspects of
the darknet and implementing methods of monitoring and collecting data in the
hopes of connecting contributions to the darknet marketplaces to and from
Canada. The significant findings include a small Canadian presence, measured
the product categories, and attribution of one cross-marketplace vendor through
data visualization. The results were made possible through a multi-stage
processing pipeline, including data crawling, scraping, and parsing. The
primary future works include enhancing the pipeline to include other media,
such as web forums, chatrooms, and emails. Applying machine learning models
like natural language processing or sentiment analysis could prove beneficial
during investigations.