This chapter provides a new foundation for data fusion based on two concepts: a conceptual framework and the goal-seeking paradigm. Data fusion can alleviate current operational problems and support development of new architectures that preserve the system characteristics. An automation system is a unique distributed real-time system that comprises a collection of sensors, actuators, controllers, communication networks, and user-interface devices. Security management in a discrete automation system is critical because of the current trends towards using open communication infrastructures. The set of actions includes options for security mechanisms that are available to a future automation system. The goal-seeking paradigm is a mechanism to represent system evolution that explicitly manages uncertainty. The goal-seeking formulation for data fusion helps to distinguish between subjective decisions that resolve uncertainty by involving humans and objective decisions that can be executed by computers. These notions are useful for critical tasks, such as security management in large-scale distributed systems.
