Artificial Neural Network Classifier for Intrusion Detection System in Computer Network

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 381)

Abstract

An intrusion detection system is a security management tool for computers and networks. An intrusion is mainly a try to violation of network security requirements and norms. Detection deals with the countermeasures to detect such attacks. The goal of the intrusion detection system mechanism is to observe the network traffic if any packet whose pattern varies when standard to the normal behavior is said to be an anomaly and hence an attack. The main objective of this paper is to perform data preprocessing on KDD CUP 99 dataset to select a subset of features to advance the speed of the detection process. A modified Kolmogorov–Smirnov correlation-based filter algorithm is used to select features. And propose an intrusion detection model using PSO-WENN; this can classify the attacks effectively and reduce the number of false alarms generated by an intrusion detection system and improve the attack detection rate.

Keywords

KDD dataset Particle swarm optimization Intrusion detection Artificial neural networks Particle swarm optimization weight extraction algorithm for a neural network classifier (PSO WENN) 

References

  1. 1.
    Anderson, P., Computer Security Threat Monitoring and Surveillance. Technical report, James P Anderson Co., Fort Washington, Pennsylvania, April 1980Google Scholar
  2. 2.
    Modeling an intrusion detection system using data mining and genetic algorithms based on fuzzy logic. IJCSNS Int. J. Comput. Sci. Netw. Secur. 8(7) 2008Google Scholar
  3. 3.
    Jones, A.K., Sielken, R.S.: Computer system intrusion detection: a survey. http://www.cs.virginia.edu/~jones/IDS-research/Documents/jones-sielken-survey-v11.pdf
  4. 4.
    Ali, K.M., Venus, W., Al Rababaa, M.S.: The Affect of Fuzzification on Neural Networks Intrusion Detection Systems, IEEE Xplore, 978-1-4244-2800-7/09Google Scholar
  5. 5.
  6. 6.
    Rajasekaran, S., Vijayalakshmi, Pai, G.A.: Neural Networks, Fuzzy Logic, and Genetic Algorithms Synthesis and ApplicationsGoogle Scholar

Copyright information

© Springer India 2016

Authors and Affiliations

  1. 1.Anil Neerukonda Institute of Technology and SciencesVisakhapatnamIndia

Personalised recommendations