AI RESEARCH
Diagnosing and Mitigating Domain Shift in Permission-Based Android Malware Detection
arXiv CS.LG
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ArXi:2605.09028v1 Announce Type: new Machine learning-based Android malware detectors often fail in real-world deployment due to domain shift, where models trained on one data source perform poorly on applications from another. This paper presents a comprehensive study on the generalizability and interpretability of permission-based detectors under cross-domain conditions.