Development of a malware detection method using a system call graph using machine learning

Abstract

Development of a malware detection method using a system call graph using machine learning

Nasser R.Z. Nasser

Incoming article date: 02.04.2023

This article is devoted to solving the problem of research and detection of malware. The method implemented in the work allows you to dynamically detect malware for Android using system call graphs using graph neural networks. The objective of this work is to create a computer model for a method designed to detect and investigate malware. Research on this topic is important in mathematical and software modeling, as well as in the application of system call control algorithms on Android devices. The originality of this direction lies in the constant improvement of approaches in the fight against malware, as well as limited information on the use of computer simulation to study such phenomena and features in the world.

Keywords: system calls, android, virus, malware, neural networks, artificial intelligence, fuzzy logic