VAEs generate synthetic malware to augment datasets, yielding reported gains in accuracy, precision, recall, and F1 for three ML classifiers.
Empirical evaluation of SMOTE in Android malware detection with machine learning: Challenges and performance in CICMalDroid 2020,
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Enhancing Malware Detection with Generative AI: Using Variational Autoencoders to Boost Machine Learning Classifiers' Performance
VAEs generate synthetic malware to augment datasets, yielding reported gains in accuracy, precision, recall, and F1 for three ML classifiers.