XAI-Droid: An Explainable Hybrid Static and Dynamic Analysis Framework for Android Adware–Trojan Malware Detection

In this paper, XAI-Droid: Explainable Hybrid Machine Learning Framework for Android Adware–Trojan Malware Detection is proposed which is a combined桐approach that explores both the static and dynamic features of APKs for detection of Android Adware–Trojan malware. To enable accurate, transparent and reproducible malware analysis, the proposed framework offers a leakage controlled learning pipeline, ensemble-based classification and SHAP inspired explainability. XAI-Droid interprets the security decisions into identifiers of influential permissions, API characteristics and runtime behaviors, which can benefit practical Android malware screening and cyber defense applications.