53966

Автор(ы): 

Амосов О. С. (ИПУ РАН, Лаборатория 40)
Амосова С. Г. (ИПУ РАН, Лаборатория 80)
Иванов Ю. С. (ФГБОУ ВО "КнАГУ", кафедра "Промышленная электроника")
Жиганов С. В. (ФГБОУ ВО "КнАГУ")

Автор(ов): 

4

Параметры публикации

Тип публикации: 

Доклад

Название: 

The Use of Deep Neural Networks to Recognize Network Traffic Abnormalities in Enterprise Information and Telecommunication Systems

ISBN/ISSN: 

978-1-7281-1730-0

DOI: 

10.1109/MLSD.2019.8911112

Наименование конференции: 

  • 2019 12th International Conference "Management of Large-Scale System Development" (MLSD)

Наименование источника: 

  • Proceedings of the 12th International Conference "Management of Large-Scale System Development" (MLSD)

Город: 

  • Москва

Издательство: 

  • IEEE

Год издания: 

2019

Страницы: 

https://ieeexplore.ieee.org/document/8911112
Аннотация
It is proposed to recognize the network traffic abnormalities by using different deep neural network architectures. The experiment in detecting DoS attacks was conducted. The influences of neural networks layers combinations on the accuracy characteristics are revealed. New is the strengthening of the classification, through the reinforcement of input vector to its cluster evaluation.

Библиографическая ссылка: 

Амосов О.С., Амосова С.Г., Иванов Ю.С., Жиганов С.В. The Use of Deep Neural Networks to Recognize Network Traffic Abnormalities in Enterprise Information and Telecommunication Systems / Proceedings of the 12th International Conference "Management of Large-Scale System Development" (MLSD). М.: IEEE, 2019. С. https://ieeexplore.ieee.org/document/8911112.