MiMaLo: advanced normalization method for mobile malware detection

Sriyanto and Sahib @ Sahibuddin, Shahrin and Abdollah, Mohd Faizal and Suryana, Nanna and Suhendra, Adang (2022) MiMaLo: advanced normalization method for mobile malware detection. International Journal of Modern Education and Computer Science (IJMECS), 14 (5). pp. 24-33. ISSN 2075-0161

Text IJMECS-V14-N5-3.PDF Download (518kB)

Abstract

A range of research procedures have been executed to overcome malware attacks. This research used a malware behavior observe approach on device calls on mobile devices operating gadget kernel. An application used to be mounted on mobile gadget to gather facts and processed them to get dataset. This research used data mining classification approach method and validates it using ten fold cross validation. MiMaLo is a method to normalize a dataset the usage of the min-max aggregate and logarithm function. The application of the MiMaLo method aims to increase the accuracy value. Derived from the experiments, the classifiers overall performance level used to be extensively increasing. The application of the MiMaLo method using the neural network algorithm produces an accuracy of 93.54% with AUC of 0.982.

Item Type:	Article
Uncontrolled Keywords:	Malware attack, Mobile malware detection, Normalization methods, MiMaLo
Divisions:	Faculty of Information and Communication Technology
Depositing User:	mr eiisaa ahyead
Date Deposited:	28 Feb 2023 08:12
Last Modified:	28 Feb 2023 08:12
URI:	http://eprints.utem.edu.my/id/eprint/26498
Statistic Details:	View Download Statistic

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