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AIDeM: Agent-Based Intrusion Detection Mechanism: Profile on PlumX
Title: AIDeM: Agent-Based Intrusion Detection Mechanism
Authors: Pinzón, Cristian
Navarro, Martí
Bajo Pérez, Javier
Keywords: Computer Science
Issue Date: 2010
Publisher: Springer Science + Business Media
Citation: Trends in Practical Applications of Agents and Multiagent Systems Advances in Intelligent and Soft Computing. Advances in Intelligent and Soft Computing. Volumen 71, pp. 347-354.
Abstract: The availability of services can be comprimised if a service request sent to the web services server hides some form of attack within its contents. This article presents AIDeM (An Agent-Based Intrusion Detection Mechanism), an adaptive solution for dealing with DoS attacks in Web service environments. The solution proposes a two phased mechanism in which each phase incorporates a special type of CBR-BDI agent that functions as a classifier. In the first phase, a case-based reasoning (CBR) engine utilizes a Naïves Bayes strategy to carry out an initial filter, and in the second phase, a CBR engine incorporates a neural network to complete the classification mechanism. AIDeM has been applied within the FUSION@ architecture to improve its current security mechanism. A prototype of the architecture was developed and applied to a case study. The results obtained are presented in this study.
ISBN: 978-3-642-12432-7 (Print) / 978-3-642-12433-4 (Online)
ISSN: 1867-5662 (Print) / 1867-5670 (Online)
Appears in Collections:BISITE. Congresos

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