Comparison of Cascading Effects in Critical Infrastructure Networks based on Simulation

Assessing impacts of threats to critical infrastructures is challenging due to the high complexity. Using probabilistic simulations seems adequate to capture the uncertainty but makes it at the same time more challenging to compare different situations. Such comparison is particularly important when actions for improved protection are considered. We here propose a simulation that gives a probability distribution over a (finite) set of states and to compare the probability distributions in such a way that actions with lower chance of worst-case damage are preferred. The approach is illustrated with data from the H2020 project PRECINCT where the impact of a flooding on a city is investigated.