Zhou, Guo and Miao, Fahui and Tang, Zhonghua and Zhou, Yongquan and Luo, Qifang (2023) Kohonen neural network and symbiotic-organism search algorithm for intrusion detection of network viruses. Frontiers in Computational Neuroscience, 17. ISSN 1662-5188
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Abstract
Introduction: The development of the Internet has made life much more convenient, but forms of network intrusion have become increasingly diversified and the threats to network security are becoming much more serious. Therefore, research into intrusion detection has become very important for network security.
Methods: In this paper, a clustering algorithm based on the symbiotic-organism search (SOS) algorithm and a Kohonen neural network is proposed.
Results: The clustering accuracy of the Kohonen neural network is improved by using the SOS algorithm to optimize the weights in the Kohonen neural network.
Item Type: | Article |
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Subjects: | Lib Research Guardians > Medical Science |
Depositing User: | Unnamed user with email support@lib.researchguardians.com |
Date Deposited: | 27 Mar 2023 09:01 |
Last Modified: | 23 Apr 2024 12:11 |
URI: | http://journal.edit4journal.com/id/eprint/530 |