With respect to traditional ones, virtualized networks enable an increased level of automation, which can be exploited to obtain network solutions that are not only more adaptive to changes, but also less prone to human errors. In this context, we are assisting at some first research attempts to exploit network virtualization to automate and optimize the allocation and configuration of network security mechanisms. However, these attempts are still quite limited compared to what could be achieved with these paradigms. One of the aspects that needs further investigation is how traffic flows and network functions can be modelled efficiently in order to forecast the behaviour of a network that may be made of different components, including stateful ones.