Abstract
Android security permissions are built-in security features that constrain what an app can do and access on the system, that is, its privileges. Permissions have been widely used for Android malware detection, mostly in combination with other relevant app attributes. The available set of permissions is dynamic, refined in every new Android OS version release. The refinement process adds new permissions and deprecates others. These changes directly impact the type and prevalence of permissions requested by malware and legitimate applications over time. Furthermore, malware trends and benign apps’ inherent evolution influence their requested permissions. Therefore, the usage of these features in machine learning-based malware detection systems is prone to concept drift issues. Despite that, no previous study related to permissions has taken into account concept drift. In this study, we demonstrate that when concept drift is addressed, permissions can generate long-lasting and effective malware detection systems. Furthermore, the discriminatory capabilities of distinct set of features are tested. We found that the initial set of permissions, defined in Android 1.0 (API level 1), are sufficient to build an effective detection model, providing an average 0.93 F1 score in data that spans seven years. In addition, we explored and characterized permissions evolution using local and global interpretation methods. In this regard, the varying importance of individual permissions for malware and benign software recognition tasks over time are analyzed.
Original language | English |
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Pages (from-to) | 65-96 |
Number of pages | 32 |
Journal | Journal of Computer Virology and Hacking Techniques |
Volume | 19 |
Issue number | 1 |
DOIs | |
Publication status | Published - Mar 2023 |
Externally published | Yes |
Keywords
- Android
- Concept drift
- Machine learning
- Malware detection
- Mobile security
- Permission
ASJC Scopus subject areas
- Computer Science (miscellaneous)
- Software
- Hardware and Architecture
- Computational Theory and Mathematics