Integrated Network Attack Fusion System (INAFS)

Today’s information age relies on an extensive network of systems that form the Global Information Grid (GIG). The GIG is threatened by numerous entities including terrorist organizations, hackers sympathetic to America’s enemies, criminal organizations, and nation states interested in cyber warfare capabilities. The ability to prevent, detect, and respond to these cyber attacks is a crucial component for the protection of our computer networks and the mission critical software that relies on them. Network monitoring and management systems provide copious amounts of data regarding the status and health of computer networks. Intelligent information filtering and fusion systems are required in order to analyze this data to detect threats, analyze their source, and provide responses to these threats. Here we propose an Integrated Network Attack Fusion System (INAFS) to support cyber attack assessment and defense. Our approach leverages three synergistic technologies: intelligent agent-based information retrieval of network data; a rule-based mechanism for event, alert, and suggested responses generation based on retrieved information and current network assessment; and a Bayesian belief network approach to cyber attack detection and assessment. We see considerable potential for this approach in ensuring network survivability from cyber attack and maintaining continuity of operations.