A taxonomy and re-implementation study of 12 ML Android malware detectors finds persistent vulnerabilities to malware evolution and adversarial attacks due to insufficient capture of malware semantics.
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Industry AI practitioners view model quality through nine attributes with context-dependent priorities, where data imbalance is a key challenge addressed by strategies like active learning, as confirmed by interviews and a follow-up survey.
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Unraveling the Key of Machine Learning-based Android Malware Detection
A taxonomy and re-implementation study of 12 ML Android malware detectors finds persistent vulnerabilities to malware evolution and adversarial attacks due to insufficient capture of malware semantics.
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Industry Practitioners Perspectives on AI Model Quality: Perceptions, Challenges, and Solutions
Industry AI practitioners view model quality through nine attributes with context-dependent priorities, where data imbalance is a key challenge addressed by strategies like active learning, as confirmed by interviews and a follow-up survey.