A static analysis approach for Android permission-based malware detection systems.

ABSTRACT: The evolution of malware is causing mobile devices to crash with increasing frequency. Therefore, adequate security evaluations that detect Android malware are crucial. Two techniques can be used in this regard: Static analysis, which meticulously examines the full codes of applications, and dynamic analysis, which monitors malware behaviour. While both perform security evaluations successfully, there is still room for improvement. The goal of this research is to examine the effectiveness of static analysis to detect Android malware by using permission-based features. This study proposes machine learning with different sets of classifiers was used to evaluate Android malware detection. The feature selection method in this study was applied to determine which features were most capable of d

SUBMITTER: Mohamad Arif J 

PROVIDER: S-EPMC8483345 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature