A New Type of Self-Adaptive Mechanism for Network Survivability Based on Intrusion Deception

In this paper, a new type of self-adaptation mechanism for survivability is proposed. It incorporates intrusion deception and uses it for unknown attack data collection. Attack information is extracted from the collected data through behavior analysis. Different measures are taken to deal with different types of attacks to form new rules. For example, signature generation is used against vulnerability utilization and slammer attacks. Then, the new rules are embedded into the network system to make it self-adaptive against unknown attacks. The concept system of this type of mechanism, its automata model and related formal description and the implementation of the key components are illustrated in this paper.