Reference : Adaptive and Dynamic Intrusion Detection by Means of Idiotypic Networks Paradigm

	Document type :	Scientific congresses, symposiums and conference proceedings : Paper published in a journal
	Discipline(s) :	Engineering, computing & technology : Computer science
	To cite this reference:	http://hdl.handle.net/10993/3301

Title :	Adaptive and Dynamic Intrusion Detection by Means of Idiotypic Networks Paradigm
Language :	English
Author, co-author :	Ostaszewski, Marek [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) >]
	Bouvry, Pascal [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) >]
	Seredynski, Franciszek [Polish Academy of Sciences > Institute for Computer Sciences]
Publication date :	2008
Journal title :	The 21th IEEE International Parallel and Distributed Processing Symposium (IPDPS), NIDISC Workshop.
Publisher :	IEEE Computer Society
Pages :	1–8
Peer reviewed :	Yes
Audience :	International
Event name :	The 21th IEEE International Parallel and Distributed Processing Symposium (IPDPS), NIDISC Workshop.
Event date :	April 2008
Keywords :	[en] Intrusion detection ; Artificial Immune Systems
Abstract :	[en] In this paper we present a novel intrusion detection architecture based on Idiotypic Network Theory (INIDS), that aims at dealing with large scale network attacks featuring variable properties, like Denial of Service (DoS). The proposed architecture performs dynamic and adaptive clustering of the network traffic for taking fast and effective countermeasures against such high-volume attacks. INIDS is evaluated on the MIT'99 dataset and outperforms previous approaches for DoS detection applied to this set.
Target :	Researchers
Permalink :	http://hdl.handle.net/10993/3301

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