Abstract
Cyber attack detection and classification is major challenge for web and network security. The increasing data traffic in network and web invites multiple cyber attack. The dynamic nature and large number of attribute of cyber data faced a problem of detection and prevention. In current research trend various method and framework are proposed by different authors. These framework and proposed method is based on data mining and neural network approach. Data mining offers various techniques such as clustering, classification, rule generation and temporal event mining; these techniques are very efficient for detection process of cyber attack. The application of neural network in cyber attack classification use as feature reduction technique. Feature reduction is very important task in cyber attack classification; because the cyber attack data consists of huge amount of features. This paper presents various method of cyber attack detection and classification technique based on data mining and neural network approach along with IDS evaluation criteria and dataset used for validated of IDS is also discussed here.
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