Development of a Neural Network Module for Detecting Network Threats in Traffic Based on Convolutional and Recurrent Neural Networks-Reference-Cited by-同舟云学术

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Development of a Neural Network Module for Detecting Network Threats in Traffic Based on Convolutional and Recurrent Neural Networks

Published:2024-01-29 Issue: Volume:5 Page:28-31
ISSN:
Container-title:2024 Conference of Young Researchers in Electrical and Electronic Engineering (ElCon)
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Author:

Volkov Alexey¹,Sobko Sergey¹,Sviridov Igor¹,Baskakov Alexandr¹,Fride Denis¹

Affiliation:

1. National Research University of Electronic Technology – MIET,Moscow,Russia

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10467195/10468070/10468509.pdf?arnumber=10468509

Reference11 articles.

1. Model» processa obrabotki sobytij informacionnoj bezopasnosti;Gajnov;Sovremennaya nauka: Aktual’nye problemy teorii i praktiki. Seriya: Estestvennye i tekhnicheskie nauki 3-4,2017

2. Sobytijnoorientirovannaya politika bezopasnosti i formal’naya model’ mekhanizma zashchity kriticheskih informacionnyh infrastruktur;Erohin;Trudy uchebnyh zavedenij svyazi,2019

3. A study on NSL-KDD dataset for intrusion detection system based on classification algorithms;Dhanabal;International journal of advanced research in computer and communication engineering,2015

4. A detailed analysis on NSL-KDD dataset using various machine learning techniques for intrusion detection;Revathi;International Journal of Engineering Research & Technology (IJERT),2013

5. From CIC-IDS2017 to LYCOS-IDS2017: A corrected dataset for better performance

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