Attack-Defense Quantification Based On Game-Theory
This work addresses the need for more comprehensive and accurate quantitative evaluation of defensive measures in cybersecurity, though it appears incremental as it builds on existing game-theoretic approaches.
The authors tackled the problem of accurately quantifying attack-defense behaviors in network security by proposing an attack-defense stochastic game model (ADSGM) and a utility calculation method, demonstrating its effectiveness through a case study that showed impacts of active defense and attack exposure risks.
With the developing of the attack and defense technology, the cyber environment has been more and more sophisticated. We failed to give an accurate evaluation of network security situation, as we lack a more accurate quantitative evaluation of attack-defense behaviors. In response to this situation, we proposed an attack-defense stochastic game model (ADSGM), analyzed the different security property of distinct defense mechanism, and put forward a corresponding utility calculation coping with the distinct defense mechanism. Through a case study, we showed the impact of active defense and the risk of attack exposure, demonstrated the effectiveness of our methods on attack-defense behavior quantification. This paper filled with the gap in the quantitative assessment of defensive measures, to make the quantitative evaluation of attack-defense more comprehensive and accurate.