Darknet Mining and Game Theory for Enhanced Cyber Threat Intelligence
By John Robertson, Ahmad Diab, Ericsson Marin, Eric Nunes, Vivin Paliath, Jana Shakarian, Paulo Shakarian [1] Arizona State University
| August 01, 2018
Due to a recent increase in popularity, Darknet hacker marketplaces and forums now provide a rich source of cyber threat intelligence for security analysts. This paper offers background information on Darknet hacker communities and their value to the cybersecurity community before detailing an operational data-collection system that is currently gathering over 300 threat warnings per week, with a precision of around 90% (Nunes 2016). Additionally, we introduce a game theoretic framework designed to leverage the exploit data mined from the Darknet to provide system-specific policy recommendations. For the framework, we provide complexity results, provably near-optimal approximation algorithms, and evaluations on a dataset of real-world exploits.
Darknet Mining and Game Theory for Enhanced Cyber Threat Intelligence