Design of an Intrusion Detection System Using Methods Based On Intelligent Systems

Authors

20.1001.1.27174409.1399.3.1.4.9/DOR

Abstract

Humans are going through a period of their history that computer systems have become an integral part of his life. Computer systems, particularly computer networks, have played a crucial role in many aspects of today's life, so their security is highly regarded. In order to cover their security and the so - called penetration detection in computer networks, many methods such as artificial neural networks are proposed, but one of the challenges of neural networks is to fall into local. The main reason for this problem is the use of slope - based methods in the training process, which is therefore used to solve this challenge by many optimization methods. In this paper, we have tried to train a multilayer perceptron neural network using the colonial competition algorithm and in order to evaluate its efficiency, the proposed method is compared with two other methods. The results of the proposed method have improved 10 - 15 % improvement in cases where the number of samples was higher.

Keywords

References

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History

  • Receive Date: 24 October 2020
  • Revise Date: 18 December 2020
  • Accept Date: 01 February 2021

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