A Game Theoretic Approach to Cyber Attack Prediction

The area investigated by this project is cyber attack prediction. With a focus on correlation-based prediction, current attack prediction methodologies overlook the strategic nature of cyber attack-defense scenarios. As a result, current cyber attack prediction methodologies are very limited in predicting strategic behaviors of attackers in enforcing nontrivial cyber attacks such as DDoS attacks, and may result in low accuracy in correlation-based predictions. This project develops a game theoretic framework for cyber attack prediction, where an automatic game-theory-based attack prediction method is proposed. Being able to quantitatively predict the likelihood of (sequences of) attack actions, our attack prediction methodology can predict fine-grained strategic behaviors of attackers and may greatly improve the accuracy of correlation-based prediction. To our best knowledge, this project develops the first comprehensive framework for incentive-based modeling and inference of attack intent, objectives, and strategies; and this project develops the first method that can predict fine-grained strategic behaviors of attackers. The significance of this research and the benefit to the public can be demonstrated to certain extent by (a) the severe threat of cyber attacks to the critical infrastructures of the nation, including many infrastructures overseen by the Department of Energy, (b) the importance of cyber security to critical infrastructure protection, and (c) the importance of cyber attack prediction to achieving cyber security.