A New Android Malware Detection Approach Using Multilayer Stacking

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Nikkhah Hossein; Ghazizadeh Ahsaee Mostafa; Mirvaziri Hamid

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Seminar Paper

Paper Information

Seminar: INTERNATIONAL CONFERENCE ON WEB RESEARCH
Year:2024 | Issue:10

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Title

A New Android Malware Detection Approach Using Multilayer Stacking

Author(s)

Nikkhah Hossein | Ghazizadeh Ahsaee Mostafa | Mirvaziri Hamid

Keywords

android

malware detection

multilayer stacking

Random Forest

Anova

Abstract

The increasing expansion of mobile phones along with the expansion of the possibilities of these phones has provided a suitable field for information theft. android is undoubtedly the most popular and widespread operating system of mobile phones, which has become the target audience of many malware authors due to this expansion. This article seeks to provide a suitable and powerful solution for detecting malware. Data processing uses a combined feature selection operation. This idea extracts the most important features and improves the accuracy and speed of detection. Then, three-level stacking is used for the detection stage. This method can significantly improve the accuracy and power of generalization compared to other methods based on the innovative idea of dataset separation. The accuracy of this method is equal to 99. 5.

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APA: Copy

Nikkhah, Hossein, Ghazizadeh Ahsaee, Mostafa, & Mirvaziri, Hamid. (2024). A New Android Malware Detection Approach Using Multilayer Stacking. INTERNATIONAL CONFERENCE ON WEB RESEARCH. SID. https://sid.ir/paper/1147370/en

Vancouver: Copy

Nikkhah Hossein, Ghazizadeh Ahsaee Mostafa, Mirvaziri Hamid. A New Android Malware Detection Approach Using Multilayer Stacking. 2024. Available from: https://sid.ir/paper/1147370/en

IEEE: Copy

Hossein Nikkhah, Mostafa Ghazizadeh Ahsaee, and Hamid Mirvaziri, “A New Android Malware Detection Approach Using Multilayer Stacking,” presented at the INTERNATIONAL CONFERENCE ON WEB RESEARCH. 2024, [Online]. Available: https://sid.ir/paper/1147370/en

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