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Android Malware Category and Family Detection and Identification using Machine Learning

Android malware is one of the most dangerous threats on the internet, and its prevalence has increased dramatically in recent years. Experts in cybersecurity face an open problem. There are a variety of machine learning-based approaches for detecting and classifying Android malware. This article offers a Machine Learning Model that uses feature selection and a Machine Learning Classifier to successfully perform malware classification and characterization techniques.

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Cite this as

Ahmed Hashem El Fiky, Ayman El Shenawy, Mohamed Ashraf Madkour (2024). Dataset: Android Malware Category and Family Detection and Identification using Machine Learning. https://doi.org/10.57702/8n3pify8

DOI retrieved: December 16, 2024

Additional Info

Field Value
Created December 16, 2024
Last update December 16, 2024
Defined In https://doi.org/10.48550/arXiv.2107.01927
Author Ahmed Hashem El Fiky
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Ayman El Shenawy
Mohamed Ashraf Madkour
Homepage https://doi.org/10.1109/ACCESS.2020.2969113