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We explore the idea of applying machine learning techniques to automatically infer risk-adaptive policies to reconfigure a network security architecture when the context in which it operates changes. To illustrate our approach, we consider the case of a MANET where nodes carrying sensitive services (e.g., web servers, key repositories, etc.) should consider relocating themselves into a different node to guarantee proper functioning. We use simulation to derive properties from a candidatedoi:10.1109/cit.2010.168 dblp:conf/IEEEcit/TapiadorC10 fatcat:wgbqm3bdz5h43gmkl5cfmezr7u