A Probabilistic Model to Predict the Survivability of SCADA Systems
Carlos Queiroz, Abdun Naser Mahmood, Zahir Tari · IEEE Transactions on Industrial Informatics · 2012
Recent spate of cyber attacks against critical infrastructure systems, which are vital to society, have shown that in addition to be infeasible to stop every possible attack it is imperative to keep such systems running. Survivability models and tools are good to evaluate system's capacity to handling undesired events. Current survivability measurement techniques are limited, since they only use performance to model system behaviour, and do not take into account service interdependencies. This paper introduces a probabilistic model that offers a new direction in measuring survivability. The proposed model solves the issues with current models by combining the formalism of Bayesian networks with information diversity. Service interdependencies are properly taken into account and the information diversity metric is used to represent service behaviour. In addition, the model is evaluated through a simulation of a SCADA system, where the entire process to construct and to use the model is detailed.