@article{Panigrah_Ranjan Patra_2014, title={Enhancing the Capability of IDS using Fuzzy Rough Classifier with Genetic Search Feature Reduction}, volume={2}, url={https://journals.scholarpublishing.org/index.php/TNC/article/view/97}, DOI={10.14738/tnc.22.97}, abstractNote={<p>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</p>}, number={2}, journal={Discoveries in Agriculture and Food Sciences}, author={Panigrah, Ashalata and Ranjan Patra, Manas}, year={2014}, month={Apr.}, pages={01–13} }