Aug 2026· Jurnal Penelitian Pendidikan IPA· Vol 12, pp. 243-251· 0 citations· 14 references
TL;DR
The average accuracy results in this study with four scenarios using the Random Forest method is 96%, and the f1-score value is 94%.
Abstract
This study detected malware on the Android operating system using a system called (syscall). Remote Access Trojan Malware Analysis on the Android operating system using Reverse Engineering Methods helps discover the technological principles of a device, object, or system by analyzing its structure, functions, and operation. This method employed dynamic analysis, namely running every malware on the Android operating system to get information on the system call (syscall) that is running. The results of the system call (syscall) information were selected using the Machine Learning selection feature using the Random Forest method. The purpose of this study is to determine the characteristics based on the system call (syscall) and the detection system's accuracy for the characteristics of Remote Access Trojan malware on the Android operating system. The average accuracy results in this study with four scenarios using the Random Forest method is 96%, and the f1-score value is 94%. This accuracy value is quite good and can be implemented in detecting remote access Trojan malware based on system call (syscall) on the Android Operating System
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