Classification of Malicious Network Traffic using Optimal Datasets for Machine Learning

Citation

Lim, Mei Shyan and Ho, Sin Ban and Chai, Ian (2022) Classification of Malicious Network Traffic using Optimal Datasets for Machine Learning. In: Postgraduate Colloquium December 2022, 1-15 December 2022, Multimedia University, Malaysia. (Unpublished)

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Abstract

Research Background Problem Statement • The first defence mechanism in an organization is the network security level. • Firewalls, Intrusion Detection Systems (IDSs) or Network Intrusion Detection Systems (NIDs) and Intrusion Prevention Systems (IPSs) are examples of the network security defence mechanism. • Network security given the most emphasis in the adoption of Artificial Intelligence (AI) and Machine Learning (ML). • Detection of malware or malicious flow at network security level using machine learning approach is explored.

Item Type: Conference or Workshop Item (Poster)
Uncontrolled Keywords: Machine Learning
Subjects: Q Science > Q Science (General) > Q300-390 Cybernetics
Divisions: Faculty of Computing and Informatics (FCI)
Depositing User: Ms Suzilawati Abu Samah
Date Deposited: 19 Dec 2022 09:04
Last Modified: 19 Dec 2022 09:05
URII: http://shdl.mmu.edu.my/id/eprint/10930

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