Creating Proactive Cyber Threat Intelligence with Hacker Exploit Labels: A Deep Transfer Learning Approach

This study introduces DTL-EL, a machine-learning system that automatically reads the exploits hackers post in online forums and labels what kind of threat each one is. To make its labels more accurate, it borrows knowledge from related sources such as darknet marketplaces and public exploit databases. In testing, it classified exploits more accurately than existing methods, helping defenders prioritize the most dangerous threats faster.