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        Networks security measures using neuro-fuzzy agents

        Author
        Abouzakhar, Nasser
        Manson, Gordon
        Attention
        2299/13549
        Abstract
        The growing dependence of modern society on telecommunication and information networks and e-type systems has become inevitable. However, those types of systems are vulnerable to malicious attacks. The speed and automation in network attack techniques continue to increase. An achievable automated attack or unauthorised access to a particular organization network could lead to devastating effects on its reputation and imminent loss of life. In this paper an innovative way is proposed to detect network attacks of a distributed nature such as denial of service (DoS) attacks. The proposed scheme is mainly based on neuro-fuzzy intelligence in order to learn and determine the fuzzy parameter functions that represent network traffic behaviour. Neuro-fuzzy agents combine the features of fuzzy logic and neural networks and they have been proposed to overcome the limitations of human expertise in defining fuzzy membership functions, especially for complex environments, such as information networks.
        Publication date
        2003
        Published in
        Information Management & Computer Security
        Published version
        https://doi.org/10.1108/09685220310463713
        Other links
        http://hdl.handle.net/2299/13549
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