Converting HMM hidden-state sequences into images and classifying them with a CNN yields 0.9781 accuracy on a 7-family Malicia subset, a 0.0023 gain over the authors' HMM-RF baseline.
Hidden Markov models for malware classification
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Malware Classification using a Hybrid Hidden Markov Model-Convolutional Neural Network
Converting HMM hidden-state sequences into images and classifying them with a CNN yields 0.9781 accuracy on a 7-family Malicia subset, a 0.0023 gain over the authors' HMM-RF baseline.