Biblio

This paper considers network protection games for a heterogeneous network system with N nodes against cyber-attackers of two different types of intentions. The first type tries to maximize damage based on the value of each net-worked node, while the second type only aims at successful infiltration. A defender, by applying defensive resources to networked nodes, can decrease those nodes' vulnerabilities. Meanwhile, the defender needs to balance the cost of using defensive resources and potential security benefits. Existing literature shows that, in a Nash equilibrium, the defender should adopt different resource allocation strategies against different types of attackers. However, it could be difficult for the defender to know the type of incoming cyber-attackers. A Bayesian game is investigated considering the case that the defender is uncertain about the attacker's type. We demonstrate that the Bayesian equilibrium defensive resource allocation strategy is a mixture of the Nash equilibrium strategies from the games against the two types of attackers separately.

Security attacks present unique challenges to self-adaptive system design due to the adversarial nature of the environment. However, modeling the system as a single player, as done in prior works in security domain, is insufficient for the system under partial compromise and for the design of fine-grained defensive strategies where the rest of the system with autonomy can cooperate to mitigate the impact of attacks. To deal with such issues, we propose a new self-adaptive framework incorporating Bayesian game and model the defender (i.e., the system) at the granularity of components in system architecture. The system architecture model is translated into a Bayesian multi-player game, where each component is modeled as an independent player while security attacks are encoded as variant types for the components. The defensive strategy for the system is dynamically computed by solving the pure equilibrium to achieve the best possible system utility, improving the resiliency of the system against security attacks.