Intrusion detection models using enhanced denoising autoencoders and lightgbm classifier with improved detection performance

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Intrusion detection models using enhanced denoising autoencoders and lightgbm classifier with improved detection performance

An intrusion detection system (IDS) is a software developed to monitor network traffic for suspicious activities to secure data transmission. The conventional IDS strategies are vulnerable to distorted high dimensional network traffic. To overcome this, we proposed an IDS that combines a denoising a...

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Bibliographic Details
Main Author:	Sheikh, Abdul Hameed
Format:	Final Year Project / Dissertation / Thesis
Published:	2023
Subjects:	TA Engineering (General). Civil engineering (General) TK Electrical engineering. Electronics Nuclear engineering
Online Access:	http://eprints.utar.edu.my/6233/ http://eprints.utar.edu.my/6233/1/SHEIKH_ABDUL_HAMEED.pdf

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