Gaussian Mixture Model Based Machine Learning Approach for Detection of Threat Types in Communication Networks-Reference-Cited by-同舟云学术

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Gaussian Mixture Model Based Machine Learning Approach for Detection of Threat Types in Communication Networks

Published:2023-09-26 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE 13th International Conference on Electronics and Information Technologies (ELIT)
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Author:

Holubnychyi Oleksii¹,Zaliskyi Maksym¹,Solomentsev Oleksandr¹,Ostroumov Ivan²,Averyanova Yuliya²,Sushchenko Olha³

Affiliation:

1. National Aviation University,Telecommunication and Radioelectronic Systems Department,Kyiv,Ukraine

2. National Aviation University,Air Navigation Systems Department,Kyiv,Ukraine

3. National Aviation University,Aerospace Control Systems Department,Kyiv,Ukraine

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10310175/10310663/10310785.pdf?arnumber=10310785

Reference32 articles.

1. Attack Vectors and Susceptibilities of the Modbus in TCP/IP Model

2. Application Areas of Positioning

3. AI in 5G Networks: Challenges and Use Cases

4. Security in 5G Wireless Networks

5. Drop deformation estimate with multi-polarization radar

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1. Self-organization Technique with a Norm Transformation Based Filtering for Sustainable Infocommunications Within CNS/ATM Systems;Lecture Notes in Networks and Systems;2024

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