Improving the content of the special course “Information Security” during the training process: detecting cyber attacks using machine learning

Abstract

Currently, as a result of the development of information and communication technologies, facts are being revealed that the detection of information attacks using existing traditional methods is ineffective. Meanwhile, machine learning algorithms find effective solutions to problems such as classifying Internet Protocol traffic, filtering malformed traffic to detect attacks, and responding to trivial attacks. Therefore, our research work was based on improving the content of a special course on information security of the educational program «6B01511-Informatics» of the L. N.Gumilyov Eurasian National University in accordance with the development of modern information technologies. Accordingly, the goal of the research work is to identify cyber-attacks using neural networks. In accordance with the purpose of the research work, work was carried out such as collecting data with cyber-attacks, classifying data into classes, developing a neural network model, identifying cyber-attacks based on the developed model. The developed model can be used to define any process in any area. According to the survey results, we see that the level of student satisfaction with the content of the special course increased by 55%. Thus, improving the content of education in the field of information security has yielded positive results. In the future, the updated special course will be available to the country's leading higher education institutions.

Keywords: neural networks, cyber-attack, machine learning, educational system, multilayer perceptron.