A Context-Aware Android Malware Detection Approach Using Machine Learning
The Android platform has become the most popular smartphone operating system, which makes it a target for malicious mobile apps. This paper proposes a machine learning-based approach for Android malware detection based on application features. Unlike many prior research that focused exclusively on A...
Main Authors: | Mohammed N. AlJarrah, Qussai M. Yaseen, Ahmad M. Mustafa |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2022-11-01
|
Series: | Information |
Subjects: | |
Online Access: | https://www.mdpi.com/2078-2489/13/12/563 |
Similar Items
-
Android Malware Detection Based on API Pairing
Published: (2020-10-01) -
Three-Phase Detection and Classification for Android Malware Based on Common Behaviors
by: Ying-Dar Lin, et al.
Published: (2016-09-01) -
Machine-Learning-Based Android Malware Family Classification Using Built-In and Custom Permissions
by: Minki Kim, et al.
Published: (2021-11-01) -
Android Malware Detection Based on Informative Syscall Subsequences
by: Roopak Surendran, et al.
Published: (2024-01-01) -
Cross-device behavioral consistency: Benchmarking and implications for effective android malware detection
by: Alejandro Guerra-Manzanares, et al.
Published: (2022-09-01)