dc.contributor.author | Golovko, Vladimir | |
dc.contributor.author | Vaitsekhovich, Leanid | |
dc.coverage.spatial | Brest | ru_RU |
dc.date.accessioned | 2023-11-29T07:49:39Z | |
dc.date.available | 2023-11-29T07:49:39Z | |
dc.date.issued | 2006 | |
dc.identifier.citation | Golovko, V. Neural Network Techniques for Intrusion Detection / Vladimir Golovko, Leanid Vaitsekhovich // International Conference on Neural Networks and Artificial Intelligence : proceedings, Brest, 31 May – 2 June, 2006 / Edited: V. Golovko [et al.]. – Brest : BSTU, 2006. – P. 66–69 : il. – Bibliogr.: p. 69 (6 titles). | ru_RU |
dc.identifier.uri | https://rep.bstu.by/handle/data/37360 | |
dc.description | Головко Владимир, Вайцехович Леонид. Нейросетевые методы обнаружения вторжений | ru_RU |
dc.description.abstract | This paper presents the neural network approaches for building of intrusion detection system (IDS). Existing intrusion detection approaches have same limitations, namely low detection time and recognition accuracy. In order to overcome these limitations we propose several neural network systems for intrusion detection. | ru_RU |
dc.language.iso | en | ru_RU |
dc.publisher | BrSTU | ru_RU |
dc.subject | neural networks | ru_RU |
dc.subject | нейронные сети | ru_RU |
dc.subject | computer security | ru_RU |
dc.subject | компьютерная безопасность | ru_RU |
dc.subject | intrusion detection | ru_RU |
dc.subject | обнаружение вторжений | ru_RU |
dc.subject | principal component analysis | ru_RU |
dc.subject | анализ главных компонент | ru_RU |
dc.subject | multilayer perseptron | ru_RU |
dc.subject | многослойный персептрон | ru_RU |
dc.title | Neural Network Techniques for Intrusion Detection | ru_RU |
dc.title.alternative | Нейросетевые методы обнаружения вторжений | ru_RU |
dc.type | Научный доклад (Working Paper) | ru_RU |