Development of software application for network traffic analysis and intrusion detection
DOI:
https://doi.org/10.17072/1993-0550-2021-2-57-64Keywords:
information security, intrusion detection system, artificial neural networks, network traffic analyserAbstract
This paper demonstrated the use of neural networks in the development of network intrusion detection systems, described the structure of the developed software application for network traffic analysis and network attacks detection, and presented the software application results.References
Ясницкий Л.Н. Интеллектуальные системы: учебник. М.: Лаборатория знаний, 2016. 221 с.
Гамаюнов Д.Ю. Обнаружение компьютерных атак на основе анализа поведения сетевых объектов: дис… канд. физ.-мат. наук / Московский государственный университет имени М.В. Ломоносова, 2007.
Zeeshan Ahmad, Andan Shahid Khan, Cheah Wai Shiang, Johari Abdullah, Farhan Ahmad. Network intrusion detection system: A systematic study of machine learning and deep learning approaches. Wiley Online Library. 2020. DOI: 10.1002/ett.4150.
CSE-CIC-IDS2018 on AWS. // Canadian Institute for Cybersecurity. URL: https://www.unb.ca/ cic/datasets/ids-2018.html (дата обращения: 11.12.2020).
KDD Cup 1999: Computer network intrusion detection // KDD. URL: https://www.kdd.org/kdd-cup/view/kdd-cup-1999/Data (дата обращения: 10.12.2020).
The UNSW-NB15 Dataset Desctiption // UNSW. URL: https://www.unsw.adfa.edu.au/unsw-canberra-cyber/cybersecurity/ADFA-NB15-Datasets/ (дата обращения: 10.11.2020).
Ясницкий Л.Н. Интеллектуальные информационные технологии и системы: учеб.-метод. пособие / Перм. ун-т. Пермь, 2007. 271 с.
Grabusts P., Zorins A. The Influence of Hidden Neurons Factor on Neural Network Training Quality Assurance // Proceedings of the 10th International Scientific and Practical Conference. Vol. III. 2015. Vol. 76. P. 81. doi: 10.17770/etr2015vol3.213.
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Articles are published under license Creative Commons Attribution 4.0 International (CC BY 4.0).