Abstract By rapid use of the Internet and computer network all over the world makes security a major issues, so using the intrusion-detection system has become more important. All the same, the primary issues of Intrusion-Detection System (IDS) are generating high false alarm rate and fails to detect attacks, which make system security more vulnerable. This paper proposed a new concept of using Suginer Filter to identify IDS. The Takagi-Sugeno fuzzy model is structured based on Neuro- fuzzy method to generate fuzzy rules and wiener filter is used to filter out attack as a noise signal using fuzzy rule generation. These two methods are combined to detect intrusive behavior of the system. The proposed suginer filter (Sugeno+Wiener) uses completely a different research structure to identify attacks and the experiment was evaluated on live network data collected, which shows that the proposed system achieves approximately 98.46% of accuracy and reduce false alarm rate to 0.08% in detecting different real time attacks. From the obtained result it’s clear that the proposed system performs better when compared with other existing machine learning techniques.

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[20] Toosi A. and Kahani M., A new Approach to Intrusion Detection based on an Evolutionary Soft Computing Model using Neuro-fuzzy Classifiers, Computing Communication, vol. 30, no. 10, pp. 2201-2212, 2007. Revathi Sujendran received her MSc degree in computer science from St. Joseph College of Arts and Science, Cuddalore, Tamilnadu, India, in 2008 and her MPhil degree in computer science from Bharathidasan University, Trichy, Tamilnadu, India, in 2009. She is now currently pursuing her PhD degree at PG and Research, Department of Computer Science, Government Arts College, affiliated to Bharathiar University, Coimbatore, Tamilnadu, India. She has published 24 Research paper which includes national, International and conference proceedings publications. She has visited Singapore for international conference and got excellent best paper award. Her current research interests include network security, data mining, and computational intelligence. Malathi Arunachalam Graduated from Bharathidasan University in 1989 and completed M.Sc (Computer Science) in 1991 under the same University. She has also received qualified degree of M.phil and Ph.D respectively in Computer Science in the year 2002 and 2012 from Bharathiar University, Coimbatore, India. She has more than two decades of teaching experience and 14 years of research experience. She has completed a funding project by UGC. She is guiding 8 Ph.D scholars and 3 M.Phil Scholars. She has guided and produced 13 M.Phil Scholars. Currently she is working as an Assistant Professor, PG and Research Department of Computer Science, Government Arts College, Coimbatore. She has published 70 Research paper which includes national, International and conference proceedings publications. She has authored three books.