System Component-Level Self-Adaptations for Security via Bayesian Games
  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.
