Fuzzy Min-Max Neural Network-Based Intrusion Detection System

  • Azad Chandrashekhar
  • Jha Vijay Kumar
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 403)


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.


Anomaly detection Misuse detection HIDS NIDS Fuzzy min-max neural network 


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Copyright information

© Springer Nature Singapore Pte Ltd. 2017

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringBirla Institute of Technology MesraRanchiIndia

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