Evaluating Lightweight Transformers With Local Explainability for Android Malware Detection

Evaluating Lightweight Transformers With Local Explainability for Android Malware Detection

Mobile phones have evolved into powerful handheld computers, fostering a vast application ecosystem but also increasing security and privacy risks. Traditional deep learning-based Android malware detection, reliant on Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs), struggl...

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Bibliographic Details
Main Authors:	Fatima Bourebaa, Mohamed Benmohammed
Format:	Article
Language:	English
Published:	IEEE 2025-01-01
Series:	IEEE Access
Subjects:	Android BERT deep learning explainability malware LIME
Online Access:	https://ieeexplore.ieee.org/document/11028131/
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