Wireless Sensor Data Fusion for Critical Infrastructure Security

Wireless Sensor Networks (WSN) are being investigated by the research community for resilient distributed monitoring. Multiple sensor data fusion has proven as a valid technique to improve detection effectiveness and reliability. In this paper we propose a theoretical framework for correlating events detected by WSN in the context of critical infrastructure protection. The aim is to develop a decision support and early warning system used to effectively face security threats by exploiting the advantages of WSN. The research addresses two relevant issues: the development of a middleware for the integration of heterogeneous WSN (SeNsIM, Sensor Networks Integration and Management) and the design of a model-based event correlation engine for the early detection of security threats (DETECT, DEcision Triggering Event Composer & Tracker). The paper proposes an overall system architecture for the integration of the SeNsIM and DETECT frameworks and provides example scenarios in which the system features can be exploited