Determining Feature Set of DOS Attacks
Denial of service attacks are large scale co operative attacks on the networking structure. It disables servers/victims from providing services to its clients. These attacks adversely affect the network badly. Therefore they must be detected on time. IDS using classification plays a significant role in detecting such intrusions but it takes significant classification time due to large number of features. It reduces its efficiency. So in order to improve efficiency or to reduce classification time, researcher provides relevant set of features for detection of DOS attacks. For this purpose, researcher is using NSL KDD dataset and analysis is performed on orange canvas V2.6.1 data mining tool.