An Android Malware Detection System using a Knowledge-based Permission Counting Method
As the number of cases of damage caused by malicious apps increases, accurate detection is required through various detection conditions, not just detection using simple techniques. In this paper, we propose a knowledge-based machine learning method using authority information and adding its usage c...
Main Authors: | Sun-A Lee, A-Reum Yoon, Ji-Won Lee, Kwangjae Lee |
---|---|
Format: | Article |
Language: | English |
Published: |
Politeknik Negeri Padang
2022-03-01
|
Series: | JOIV: International Journal on Informatics Visualization |
Subjects: | |
Online Access: | https://joiv.org/index.php/joiv/article/view/859 |
Similar Items
-
Machine-Learning-Based Android Malware Family Classification Using Built-In and Custom Permissions
by: Minki Kim, et al.
Published: (2021-11-01) -
Permissions-Based Detection of Android Malware Using Machine Learning
by: Fahad Akbar, et al.
Published: (2022-04-01) -
Android Malware Detection Based on API Pairing
Published: (2020-10-01) -
A Context-Aware Android Malware Detection Approach Using Machine Learning
by: Mohammed N. AlJarrah, et al.
Published: (2022-11-01) -
Android malware detection with MH-100K: An innovative dataset for advanced research
by: Hendrio Bragança, et al.
Published: (2023-12-01)