Enhancing the Capability of IDS using Fuzzy Rough Classifier with Genetic Search Feature Reduction - Panigrah, Ashalata; Ranjan Patra, Manas (Discoveries in Agriculture and Food Sciences, 2014)
Rapid expansion of computer network throughout the world has made security a crucial issue in a computing environment. In the recent past several cyber attacks have corrupted data of many organizations and creating serious problems. Intrusion Detection System which are increasingly a key part of system defense are used to identify abnormal activities in a computer system. The success of an intrusion detection system depends on the selection of the appropriate features in detecting the intrusion activity. Experiments have been conducted using four classifier techniques , viz, Fuzzy NN, Fuzzy Rough NN, VQNN, Fuzzy Rough Ownership NN. We have studied the accuracy, recall, precision, false alarm rate, error rate of all the classifier techniques