Leanid U. Vaitsekhovich

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The major problem of existing models is recognition of new attacks, low accuracy, detection time and system adaptability. In this paper the method of recognition of attack class on the basis of the analysis of the network traffic is described. Our first approach is based on combination principal component analysis (PCA) neural networks and multilayer(More)
Most current Intrusion Detection Systems (IDS) examine all data features to detect intrusion. Also existing intrusion detection approaches have some limitations, namely impossibility to process a large number of audit data for realtime operation, low detection and recognition accuracy. To overcome these limitations, we apply modular neural network models to(More)
In this article the artificial immune system and neural network techniques for intrusion detection have been addressed. The AIS allows detecting unknown samples of computer attacks. The integration of AIS and neural networks as detectors permits to increase performance of the system security. The detector structure is based on the integration of the(More)
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