Critical infrastructure forms an interdependent network, where individual infrastructure sectors depend on the availability of others in order to function. In such environment, faults easily propagate through the interlinked systems causing cascading failures. In order to effectively respond to incidents at national scale, it is necessary to maintain situational awareness by creating a common operational picture over all infrastructure sectors. A suitable way of modelling critical infrastructure and the interdependencies is required for building a system capable of delivering the needed information for obtaining robust situational awareness.
This thesis presents a model of critical infrastructure for national scale situational awareness applications, as well as analysis methods for estimating current and future infrastructure status. The model uses directed graphs in conjunction with finite state transducers to present dependencies and operational status of critical infrastructure systems. Analysis method utilising graph centrality measures was developed for quantifying both system specific and infrastructure wide impact of disruptions. Additionally, an entropy based analysis method was created for estimating operational status of infrastructure systems in situations, where current data is not available.
The electric grid and mobile networks of a coastal area of Finland were modelled using the presented methods. Dataset of system failures observed during a storm, in conjunction with simulation tools were used to evaluate the suitability of the framework for situational awareness tasks. Results indicate, that the proposed modelling and analysis methods are suitable for real time situational awareness applications.
