Fuzzy cognitive maps for decision support in an automatic intrusion response mechanism

One of the key issues in developing an automatic response system is how to determine a response plan and response measures and how to make sure that they are proper when an attack is detected by an IDS. It is hard to find an exact mathematical model to describe this decision-making process because there are a lot of factors in the process and these factors interact each other. Fuzzy cognitive maps aim to mimic the reasoning process of the human. FCMs are able to capture and imitate the nature of human being in describing, representing and developing models. They are good at processing fuzzy and rough information and have adaptive, intelligent features. This paper presents a FCM-based decision support mechanism, which synthetically takes all of the related factors into account, offering objective parameters for setting up the intrusion response plan and choosing response measures. The mechanism is robust, adaptive and simple.