Behaviour Engines allow the acquisition of tacit knowledge by using a learn-by-doing workflow and provide a direct interface between the expert user and the developing project code based on an intuitive justification-conclusion language; thus surpassing legacy policy engines by being a self developing and learning mechanism. This paper seeks to formulate the current state of the art in technology and processes and attempts to merge the application of ontological decision techniques of behaviour engines with network packet capture data, to detect data exfiltration attempts over covert channelling. The final goal of the research will be to develop a behaviour engine/intrusion detection solution for pre-emptive counter-measures to anomalous behaviour from within or without a network.speed.

No abstract