Published Paper Details:

Dark web monitoring is a crucial aspect of cybersecurity and law enforcement, focusing on the surveillance and analysis of activities within the dark web, a hidden network accessible only through specialized software like Tor. This hidden network provides a haven for various illegal pursuits, including cybercrime, drug trafficking, and illicit trade. Detection, filtering, and analysis of illegal activities are essential components of dark web monitoring. Advanced technologies and methodologies, including machine learning algorithms, facilitate the identification and categorization of illicit content and behaviours across forums, marketplaces, and communication channels. Cybercriminals make full use of the hidden network called as Dark Web and they are hidden from the normal search engines which are publicly facing, to sell a variety of illicit products and services. A highly automated modular system called D-Monitor is described to help with the gathering and analysis of massive volumes of unstructured data. The system relies on a Python module named OnionSearch to collect URLs based on keywords we already define in our tool. and search through various search engines like Ahmia, tor66, and torgle. These keywords are not limited to already defined keywords, but more number of keywords can be added if required and expand our scope of data collection. The dark web's anonymity services safeguard user information protection, but they also provide the ideal setting for illicit and criminal operations including drug and gun trafficking, people trafficking, and illicit information transfers. A Python dark web monitoring crawler which is built by utilizing the tor network was created to gather and store a huge number of dark web site URLs in order to gain more information about the websites by searching using keyword parameter and find suspicious information and track criminals utilising the dark web to carry out illicit operations. The tool takes screenshots using the tbselenium module and displays them on the frontend, preserving anonymity and avoiding the need to rely on the Tor browser User Interface.