From code to security: machine learning approaches in android vulnerability detection
- 27 December 2025
- journal article
- regular contribution
- Published by Springer Nature in International Journal of Information Security
- Vol. 25 (1) , 17
Abstract
No abstract availableKeywords
This publication has 141 references indexed in Scilit:
- A Transformer Based Malicious Traffic Detection Method in Android Mobile Networks2024
- FedREVAN: Real-time DEtection of Vulnerable Android Source Code Through Federated Neural Network with XAI2024
- Android Code Vulnerabilities Early Detection Using AI-Powered ACVED Plugin2023
- Machine Learning Based Android Vulnerability Detection: A Roadmap2020
- Evading API Call Sequence Based Malware Classifiers2020
- Deep Learning-Based Vulnerable Function Detection: A Benchmark2020
- Feature-Based Semi-supervised Learning to Detect Malware from Android2020
- Obfusifier: Obfuscation-Resistant Android Malware Detection System2019
- Static, Dynamic and Intrinsic Features Based Android Malware Detection Using Machine Learning2019
- VuRLE: Automatic Vulnerability Detection and Repair by Learning from Examples2017