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dc.contributor.authorAbouzakhar, Nasser
dc.contributor.authorManson, Gordon
dc.identifier.citationAbouzakhar , N & Manson , G 2003 , ' Networks security measures using neuro-fuzzy agents ' , Information Management & Computer Security , vol. 11 , no. 1 , pp. 33-38 .
dc.description.abstractThe 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.en
dc.relation.ispartofInformation Management & Computer Security
dc.subjectNetworks, Security,Fuzzy logics, Neural networks, Hacking
dc.titleNetworks security measures using neuro-fuzzy agentsen
dc.contributor.institutionSchool of Computer Science
dc.description.statusPeer reviewed
rioxxterms.typeJournal Article/Review

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