A Lightweight and Multi-Stage Approach for Android Malware Detection Using Non-Invasive Machine Learning Techniques

A Lightweight and Multi-Stage Approach for Android Malware Detection Using Non-Invasive Machine Learning Techniques

Android has been a constant target of cybercriminals that try to attack one of the most used operating systems, commonly using malicious applications (denominated malware) that, once installed on a device, can harm users in several ways. Existing malware detection solutions are usually invasive as t...

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Bibliographic Details
Main Authors: Leonardo da Costa, Vitor Moia
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
Android
machine learning
malware detection
multi-stage analysis
non-invasive feature extraction
Online Access:https://ieeexplore.ieee.org/document/10186242/

Internet

https://ieeexplore.ieee.org/document/10186242/

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