Authors: Meryam Chaieb, Mostafa Anouar Ghorab, Mohamed Aymen Saied

Published on: May 06, 2024

Impact Score: 7.4

Arxiv code: Arxiv:2405.03620

Summary

• What is new: Introduction of BERTroid, a malware detection model based on the BERT architecture, specifically designed for Android systems.
• Why this is important: The increasing prevalence of cyber threats and malware attacks on both individuals and businesses.
• What the research proposes: BERTroid, an innovative automated machine learning solution using the BERT architecture for detecting Android malware.
• Results: BERTroid outperforms existing state-of-the-art solutions in detecting Android malware, demonstrating resilience across diverse datasets.

Technical Details

Technological frameworks used: BERT architecture

Models used: Transformers, attention-based deep learning methods

Data used: Multiple datasets evaluating Android malware

Potential Impact

Cybersecurity firms, Android ecosystem stakeholders (app developers, device manufacturers), businesses requiring malware protection

Want to implement this idea in a business?

We have generated a startup concept here: Defendex.