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cs.CR2025
CITADEL: A Semi-Supervised Active Learning Framework for Malware Detection Under Continuous Distribution Drift
Md Ahsanul Haque, Md Mahmuduzzaman Kamol, Suresh Kumar Amalapuram +2
Android malware detection systems suffer severe performance degradation over time due to concept drift caused by evolving malicious and benign app behaviors. Although recent method…
cs.CR2025
LAMDA: A Longitudinal Android Malware Benchmark for Concept Drift Analysis
Md Ahsanul Haque, Ismail Hossain, Md Mahmuduzzaman Kamol +4
Machine learning (ML)-based malware detection systems often fail to account for the dynamic nature of real-world training and test data distributions. In practice, these distributi…