Engineering Secure Self-adaptive Systems with Bayesian Games
Nianyu Li, Mingyue Zhang,
Eunsuk Kang and
David Garlan.
In Proceedings of the 24th International Conference on Fundamental Approaches to Software Engineering, 27 March - 1 April 2021.
Online links: 
Abstract
| Security attacks present unique challenges to self-adaptive
system design due to the adversarial nature of the environment. Game
theory approaches have been explored in security to model malicious
behaviors and design reliable defense for the system in a mathematically
grounded manner. However, modeling the system as a single player, as
done in prior works, 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 theory and model the defender (i.e., the system)
at the granularity of components. Under security attacks, the architecture
model of the system is translated into a Bayesian multi-player game,
where each component is explicitly modeled as an independent player
while security attacks are encoded as variant types for the components.
The optimal defensive strategy for the system is dynamically computed
by solving the pure equilibrium (i.e., adaptation response) to achieve
the best possible system utility, improving the resiliency of the system
against security attacks. We illustrate our approach using an example
involving load balancing and a case study on inter-domain routing. |
Keywords: Formal Methods, Science of Security, Self-adaptation.
@InProceedings{2021:FASE:Li,
AUTHOR = {Li, Nianyu and Zhang, Mingyue and Kang, Eunsuk and Garlan, David},
TITLE = {Engineering Secure Self-adaptive Systems with Bayesian Games},
YEAR = {2021},
MONTH = {27 March - 1 April},
BOOKTITLE = {Proceedings of the 24th International Conference on Fundamental Approaches to Software Engineering},
PDF = {http://acme.able.cs.cmu.edu/pubs/uploads/pdf/FASE2021.pdf},
ABSTRACT = {Security attacks present unique challenges to self-adaptive
system design due to the adversarial nature of the environment. Game
theory approaches have been explored in security to model malicious
behaviors and design reliable defense for the system in a mathematically
grounded manner. However, modeling the system as a single player, as
done in prior works, 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 theory and model the defender (i.e., the system)
at the granularity of components. Under security attacks, the architecture
model of the system is translated into a Bayesian multi-player game,
where each component is explicitly modeled as an independent player
while security attacks are encoded as variant types for the components.
The optimal defensive strategy for the system is dynamically computed
by solving the pure equilibrium (i.e., adaptation response) to achieve
the best possible system utility, improving the resiliency of the system
against security attacks. We illustrate our approach using an example
involving load balancing and a case study on inter-domain routing.},
KEYWORDS = {Formal Methods, Science of Security, Self-adaptation}
}
|
