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Aru, O. E.
Department of Computer Engineering, College of Engineering and Technology Michael Okpara University of Agriculture Umudike, P.M.B. 7267.Umuahia Abia State, Nigeria
ABSTRACT
Securing
a computer system can be achieved by using various methods like firewalls,
anti-virus tools, network security tools, malware removal tools, and monitoring
tools. These tools and applications need to be updated and monitored regularly
by the user. If computer users fail to update the security tools, then the
computer system may be infected by a virus or may be attacked, thereby
compromising the efficiency of the system. This paper, therefore, proposes a
learning system to provide security by identifying the operating system process
as Self and Non-Self processes. Concepts of Artificial Neural Network (ANN) Learning
have been used for the identification of processes. An Artificial Neural
Network is created by using processes parameters with random weights. These
weights are updated by using Gradient Descent Algorithm for various training
examples, and then this Artificial Neural Network is tested with test data
examples. From the result, it is observed that Artificial Neural Network
Learning provides a better approach for identifying Self and Non-Self process
and provides a better security for computer systems.
Keywords: Artificial Neural Network, Cyber Security, Weight Updates, Self and Non-Self Process, Operating Systems.
https://doi.org/10.33922/j.ujet_v7i1_7
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View: 138 | Download: 14
Published
Tuesday, June 01, 2021
Issue
Vol. 7 No. 1, June 2021
Article Section
GENERAL
The contents of the articles are the sole opinion of the author(s) and not of UJET.
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