Automated System for Detecting Cyber Bot Attacks in 5G Networks using Machine Learning

Thrupthi, C.P. and Chitra, K. and Harilakshmi, V.M. (2024) Automated System for Detecting Cyber Bot Attacks in 5G Networks using Machine Learning. Journal of Innovation and Technology, 2024 (31). pp. 1-6. ISSN 2805-5179

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Abstract

The automated system for detecting cyber bot attacks in 5G networks relies on cloud servers to store data, facilitating the global access necessary for online transactions and services, but points to the rise of cybercrime with information security flaws and human stealth Attackers known as "Botmasters" spread Trojan malware to grow bots on the network causing DDOS attacks. Botnets are compromised computer networks controlled by attackers that are visible for this reason. Machine learning algorithms have been proposed to identify bot networks with a focus on extracting features from high-dimensional datasets. However, the literature pays little attention to selection methods, which are crucial for developing effective machinelearning models.

Item Type:	Article
Uncontrolled Keywords:	Bot attacks, 5G network attacks, cyber-attacks, Botnet attacks
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software T Technology > T Technology (General) T Technology > TJ Mechanical engineering and machinery
Depositing User:	Unnamed user with email masilah.mansor@newinti.edu.my
Date Deposited:	28 Nov 2024 07:05
Last Modified:	28 Nov 2024 07:05
URI:	http://eprints.intimal.edu.my/id/eprint/2068

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