Enhancement of network security by use machine learning

Hasan, Ahmed Raheem (2019) Enhancement of network security by use machine learning. Masters thesis, Universiti Tun Hussein Onn Malaysia.

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Abstract

This research is about the design and simulation on enhancement network security using machine learning. The design use MATLAB coding to show the simulation. The coding is designed in a way that there is an attack of malicious to destroy the data. Because there is a machine-learning scheme in the security, the system have done automatically protect the data and hence the data is recovered at the end of the system. The important study in this research is the machine learning with deep learning system to enhance the security. This put the system into artificial intelligent system. By trains the system, the security can be enhanced. The next incoming data have done checked and the system was identify whether it content errors or fake data. By the end of the research, graphs and animation system have done shown to demonstrate the basic operation of the enhance network with machine learning system. From the analysis in the simulation results, one can see that the ANNDL is the best algorithm of machine learning process. This method uses many layers to compute or process the data. The time taken to reach the accuracy is also short with less number of iteration. The ANNDL uses iterations method to detect the data, do matching and identify the data. If the data is 100% matched, then the accuracy increase to 1%. As more and more iteration take places, the accuracy have done increased. Thus, it is suggests to have high number of iterations.

Item Type:	Thesis (Masters)
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5101-6720 Telecommunication. Including telegraphy, telephone, radio, radar, television
Divisions:	Faculty of Electrical and Electronic Engineering > Department of Electrical Engineering
Depositing User:	Mrs. Sabarina Che Mat
Date Deposited:	25 Jul 2021 06:27
Last Modified:	25 Jul 2021 06:27
URI:	http://eprints.uthm.edu.my/id/eprint/442

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