Critical infrastructures, like water-, gas- and electricity distribution are remotely controlled by communication networks (so-called SCADA networks). Failures of components and attacks to their control network can have a severe impact on their performance and dependability.
Stochastic hybrid systems.
In order to model critical infrastructures one needs hybrid models that combine both, discrete and continuous components (e.g. For modelling discretely controlled physical systems). Additionaly, stochastic variables are needed to describe random failure- and repair processes.
So-called stochastic hybrid systems have been successfully used in the past to model safety-critical applications. They are especially usefull to describe the evolution of physical processes in a user-friendly way.
The focus of this research group is on the development of special, analyzable model classes, which are useful to describe systems with specific characteristics. Applciation areas encompass critical infrastructures, like water-, gas- and electricity distribution.
The biggest challenge when modelling critical infrastructures lies in the size and complexity of the systems to be modelled. Many existing approaches do not scale with real systems. Hence, we focus on the development of scalable models and methods for critical infrastructures, especially when taking into account their communication networks.
Next to the development of new methods and techniques, we also develop tools that allow to compare methods and results as well as ease the modelling and evaluation of real systems. Our tools HYPEG and hpnmg investigate Hybrid Petri nets. While HYPEG provides discrete event simulation, the analytical results of hpnmg only include a numerical error.