Dynamic Security Risk Management Using Bayesian Attack Graphs

Security risk assessment and mitigation are two vital processes that need to be executed to maintain a productive IT infrastructure. On one hand, models such as attack graphs and attack trees have been proposed to assess the cause-consequence relationships between various network states, while on the other hand, different decision problems have been explored to identify the minimum-cost hardening measures. However, these risk models do not help reason about the causal dependencies between network states. Further, the optimization formulations ignore the issue of resource availability while analyzing a risk model. In this paper, we propose a risk management framework using Bayesian networks that enable a system…

• NS
  National Science Foundation
• UO
  University of Michigan
• UO
  University of Michigan-Dearborn
• AF
  Air Force Office of Scientific Research