Abstract
In this chapter, a novel intrusion detection system has been proposed which is based on the fuzzy min max neural network. The objective of the proposed intrusion detection system is to protect the end user system from the cope of various types of cyberattacks. The main hurdles in the today’s intrusion detections system are the nonlinear separablity, online adaption, preprocessing of the network logs, attribute selection, and the learning of the desired system for the anomalous or the signature detection. The proposed system is tested on the KDD Cup 99 dataset, and the classification accuracy and classification error are used for performance evaluation. The critical experiment on the proposed system gives the superior performance.
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Chandrashekhar, A., Vijay Kumar, J. (2017). Fuzzy Min-Max Neural Network-Based Intrusion Detection System. In: Nath, V. (eds) Proceedings of the International Conference on Nano-electronics, Circuits & Communication Systems. Lecture Notes in Electrical Engineering, vol 403. Springer, Singapore. https://doi.org/10.1007/978-981-10-2999-8_15
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DOI: https://doi.org/10.1007/978-981-10-2999-8_15
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