Applying QMLP and QCNN quantum classifiers to five malware datasets yields binary accuracies up to 96% and multiclass accuracy up to 95.7%, with QMLP generally more accurate and QCNN faster.
Enhancing state-of-the-art classifiers with api semantics to detect evolved android malware,
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Towards Quantum Machine Learning for Malicious Code Analysis
Applying QMLP and QCNN quantum classifiers to five malware datasets yields binary accuracies up to 96% and multiclass accuracy up to 95.7%, with QMLP generally more accurate and QCNN faster.