Publication Type : Conference Paper
Publisher : ICCCNT 2010
Source : 2010 2nd International Conference on Computing, Communication and Networking Technologies, ICCCNT 2010, Karur (2010)
ISBN : 9781424465910
Keywords : Intrusion detection, Learning algorithms, Machine learning algorithms, Noise radars, Radar, Radio, Random noise radar, Reliable systems, Software-defined radios, Support vector, Support vector machines, SVM model, Tracking radar, Training and testing
Campus : Coimbatore
School : School of Engineering
Department : Electronics and Communication
Year : 2010
Abstract : The need for reliable systems for detecting intrusions into a given area has given rise to the research and use of random noise radars. This paper deals with the issues regarding the use of such systems. The advantages of the use of such radar are illustrated followed by the actual mode of implementing the system itself. The novelty in this approach is the use a software defined radio as the platform for the system as it has a number of added advantages as have been detailed Subsequently, the intrusion detection can be viewed as a classification problem and solved using any machine learning algorithm. The paper also investigates the use of support vector machines (SVM) for the above said problem and derives a suitable model for classification. The training and testing of SVM model is in progress. ©2010 IEEE.
Cite this Research Publication : D. M. Chinnam, Madhusudhan, J., Nandhini, C., Prathyusha, S. N., Sowmiya, S., Dr. Ramanathan R., and Soman, K. P., “Intrusion detection using software defined noise radar”, in 2010 2nd International Conference on Computing, Communication and Networking Technologies, ICCCNT 2010, Karur, 2010.