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Fuzzy min–max neural network and particle swarm optimization based intrusion detection system

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Abstract

To maintain the integrity, availability, reliability of the data and services available on web requires a strong network security framework, in such consequence IDS based on data mining are the best solution. In this paper we proposed an intrusion detection system which is based on the fuzzy min max neural network and the particle swarm optimization. The proposed system is tested with the help of preprocessed KDD CUP data set. Classification accuracy and classification error are taken as a performance evaluation parameter to test the effectiveness of the system. The proposed system is compared with the some of the well-known methods, the results shows that the proposed system performed well as compared to the other systems.

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Authors and Affiliations

  1. Department of Computer Applications, National Institute of Technology, Jamshedpur, 831014, India

    Chandrashekhar Azad

  2. Department of Computer Science and Engineering, Birla Institute of Technology, Mesra, Ranchi, 835215, India

    Vijay Kumar Jha

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  1. Chandrashekhar Azad
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  2. Vijay Kumar Jha
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Correspondence to Chandrashekhar Azad.

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Azad, C., Jha, V.K. Fuzzy min–max neural network and particle swarm optimization based intrusion detection system. Microsyst Technol 23, 907–918 (2017). https://doi.org/10.1007/s00542-016-2873-8

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  • DOI: https://doi.org/10.1007/s00542-016-2873-8

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