Unsupervised learning techniques for an intrusion detection system
Proceedings of the 2004 ACM symposium on Applied computing
Analyzing Cross-Sector Interdependencies
HICSS '07 Proceedings of the 40th Annual Hawaii International Conference on System Sciences
The role of Wireless Sensor Networks in the area of Critical Information Infrastructure Protection
Information Security Tech. Report
Analysis of Security Threats, Requirements, Technologies and Standards in Wireless Sensor Networks
Foundations of Security Analysis and Design V
Adaptive Dispatching of Incidences Based on Reputation for SCADA Systems
TrustBus '09 Proceedings of the 6th International Conference on Trust, Privacy and Security in Digital Business
A security analysis for wireless sensor mesh networks in highly critical systems
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Towards early warning systems: challenges, technologies and architecture
CRITIS'09 Proceedings of the 4th international conference on Critical information infrastructures security
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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 (EWSs) and this will be precisely the main topic of this paper. More specifically, we present in this paper an EWS design based on a Wireless Sensor Network (using the ISA100.11a standard) that constantly supervises 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 system, identification of the most suitable field operator to attend an alarm, reporting of causes and responsible operators, and learning from new anomalous situations.