5th International conference on Critical Information Infrastructures Security (CRITIS’10), LNCS 6712, Springer, pp. 55-67, September, 2010.
A way of controlling a cascading effect caused by a failure or a threat in a critical system is using intelligent mechanisms capable of predicting anomalous behaviours and also capable of reacting against them in advance. These mechanisms are known as Early Warning Systems (EWS) and this will be precisely the main topic of this paper. Specially, we present an EWS design based on a Wireless Sensor Network (using the ISA100.11a standard) that constantly supervise the application context. This EWS is also based on forensic techniques to provide dynamic learning capacities. As a result, this new approach will aid to provide a reliable control of incidences by offering a dynamic alarm management, identification of the most suitable field operator to attend an alarm, reporting of causes and responsible operators, and learning from new anomalous situations.