FABLDroid: Malware detection based on hybrid analysis with factor analysis and broad learning methods for android applications
The Android operating system, which is popular on mobile devices, creates concerns for users due to the malware it is exposed to. Android allows applications to be downloaded and installed outside the official application store. Applications installed from third-party environments threaten users’ pr...
Saved in:
Main Authors: | Kazım Kılıç, İsmail Atacak, İbrahim Alper Doğru |
---|---|
Format: | Article |
Language: | English |
Published: |
Elsevier
2025-02-01
|
Series: | Engineering Science and Technology, an International Journal |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S2215098624003318 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
LinRegDroid: Detection of Android Malware Using Multiple Linear Regression Models-Based Classifiers
by: Durmus Ozkan Sahin, et al.
Published: (2022-01-01) -
Apk2Audio4AndMal: Audio Based Malware Family Detection Framework
by: Oguz Emre Kural, et al.
Published: (2023-01-01) -
MALVADA: A framework for generating datasets of malware execution traces
by: Razvan Raducu, et al.
Published: (2025-05-01) -
Transformer-based malware detection using process resource utilization metrics
by: Dimosthenis Natsos, et al.
Published: (2025-03-01) -
Métodos de programación segura en Java para aplicaciones móviles en Android
by: Rodrigo Pimienta García, et al.
Published: (2014-01-01)