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...

Full description

Saved in:
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/
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://ieeexplore.ieee.org/document/11028131/

Similar Items