SHADOW: A framework for Systematic Heuristic Analysis and Detection of Observations on the Web

The cyberspace contains vast amounts of information that are crucial for cybersecurity professionals to gather threat intelligence, prevent cyberattacks, and secure organizational networks. Unlike earlier and less targeted attacks, modern cyber-attacks are more organized and sophisticated, often targeting specific groups, which leaves many users unaware of the vulnerable resources within the cyberspace. The increasing freedom on information access in the deep and dark web has led many organizations to identify their data loose on these spaces. Therefore, creating methods to crawl and extract valuable information from the deep web is a critical concern. Some deep web content can be accessed through the surface web by submitting query forms to retrieve the needed information, but it is not as simple in all cases. This paper proposes a system of framework to identify these leaks and notify relevant parties on the same in-time.