Opensource intelligence and dark web user de-anonymisation Online publication date: Thu, 02-Mar-2023
by Tashi Wangchuk; Digvijaysinh Rathod
International Journal of Electronic Security and Digital Forensics (IJESDF), Vol. 15, No. 2, 2023
Abstract: The dark web has emerged as a platform where cybercriminals carry out illegal activities. Attempts to investigate and de-anonymise the suspicious dark web users have not been able to keep up with the pace of the dark web's flourishing coupled with dysfunctional tools and techniques. This study proposes and evaluates a dark web investigation framework using a Python-based tool to harvest data from the dark web to derive intelligence for further investigation using the available opensource intelligence (OSINT) tools. In the experimental implementation of the framework and the tool (Dark2Clear), the tool successfully scraped the hidden service URLs, harvested the e-mail addresses of the dark web users, and suspicious e-mail addresses were used as input to the OSINT tools for gathering intelligence to de-anonymise. It was observed that the framework and tool can be effectively used by the investigators to investigate and de-anonymise suspicious dark web users.
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