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 ![]() | |
Seredynski, Franciszek [Polish Academy of Sciences > Institute for Computer Sciences] | |
Bouvry, Pascal ![]() | |
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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