Intrusion detection systems are increasingly a key part of systems defense. Various approaches to intrusion detection are currently being used, but they are relatively ineffective. Artificial Intelligence plays a driving role in security services. This paper proposes a dynamic model of intelligent intrusion detection system, based on a specific AI approach for intrusion detection. The techniques that are being investigated include fuzzy logic with network profiling, which uses simple data mining techniques to process the network data. The proposed hybrid system combines anomaly and misuse detection. Simple fuzzy rules allow us to construct if-then rules that reflect common ways of describing security attacks. We use DARPA dataset for training and benchmarking. © ICS AS CR 2007.
|Number of pages||12|
|Journal||Neural Network World|
|Publication status||Published - 2007|