A survey of neural networks usage for intrusion detection systems

Anna Drewek-Ossowicka; Mariusz Pietrołaj; Jacek Rumiński

doi:10.1007/s12652-020-02014-x

A survey of neural networks usage for intrusion detection systems

Abstract

In recent years, advancements in the field of the artificial intelligence (AI) gained a huge momentum due to the worldwide appliance of this technology by the industry. One of the crucial areas of AI are neural networks (NN), which enable commer‐ cial utilization of functionalities previously not accessible by usage of computers. Intrusion detection system (IDS) presents one of the domains in which neural networks are widely tested for improving overall computer network security and data privacy. This article gives a thorough overview of recent literature regarding neural networks usage in intrusion detection system area, including surveys and new method proposals. Short tutorial descriptions of neural network architectures, intrusion detection system types and training datasets are also provided.

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Category:: Articles
Type:: artykuły w czasopismach
Published in:: Journal of Ambient Intelligence and Humanized Computing pages 1 - 18,
ISSN: 1868-5137
Language:: English
Publication year:: 2020
Bibliographic description:: Drewek-Ossowicka A., Pietrołaj M., Rumiński J.: A survey of neural networks usage for intrusion detection systems// Journal of Ambient Intelligence and Humanized Computing -, (2020), s.1-18
DOI:: Digital Object Identifier (open in new tab) 10.1007/s12652-020-02014-x
Verified by:: Gdańsk University of Technology