Reference : Coevolutionary-based Mechanisms for Network Anomaly Detection
Scientific journals : Article
Engineering, computing & technology : Computer science
http://hdl.handle.net/10993/3308
Coevolutionary-based Mechanisms for Network Anomaly Detection
English
Ostaszewski, Marek mailto [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]
Bouvry, Pascal mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) >]
2007
Journal of Mathematical Modelling and Algorithms
Springer
6
3
411-431
Yes
International
1570-1166
1572-9214
Berlin
Germany
[en] Intrusion detection ; Artificial Immune Systems ; Coevolutionary algorithms
[en] The paper presents an approach based on the principles of immune systems
applied to the anomaly detection problem. Flexibility and efficiency of the
anomaly detection system are achieved by building a model of the network
behavior based on the self-nonself space paradigm. Covering both
self and nonself spaces by hyperrectangular structures is proposed.
The structures corresponding to self-space are built using a training
set from this space. The hyperrectangular detectors covering nonself
space are created using a niching genetic algorithm. A coevolutionary
algorithm is proposed to enhance this process. The results of
experiments show a high quality of intrusion detection, which
outperform the quality of the recently proposed approach based on
a hypersphere representation of the self-space.
Researchers
http://hdl.handle.net/10993/3308

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