Keywords: computer network, neural network, security threat, deep learning, protection mechanism
Detection of information security threats using deep neural networks in computer networks in real time
UDC 004.855.5
DOI: 10.26102/2310-6018/2022.38.3.011
Currently, the issue of detecting information security threats in computer networks is becoming a problem when it comes to preventing such threats in real time. The number of subscribers of almost any computer network is growing and so does the number of threats that can create a potential danger to the functioning of the network. In this regard, modern mechanisms that will help to respond to emerging information security threats in a timely manner are required. In this paper, the analysis of possible mechanisms of protection against security threats in computer networks is carried out and a methodology for implementing such protection using neural networks is proposed. In addition, a control example is implemented with a trained deep neural network which is able to detect information security threats with high accuracy and minimal delays. The materials of the article are of practical value when incorporating such a neural network into an intrusion detection system. By means of the method proposed in the article, it is possible to achieve a near-real-time response to information security threats and, as a result, prevent possible information security accidents.
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Keywords: computer network, neural network, security threat, deep learning, protection mechanism
For citation: Trunov E.E., Klyuev S.G. Detection of information security threats using deep neural networks in computer networks in real time. Modeling, Optimization and Information Technology. 2022;10(3). URL: https://moitvivt.ru/ru/journal/pdf?id=1212 DOI: 10.26102/2310-6018/2022.38.3.011 (In Russ).
Received 09.07.2022
Revised 24.08.2022
Accepted 15.09.2022
Published 30.09.2022