To believe or not to believe: Validating explanation fidelity for dynamic malware analysis

30 Apr 2019 Li Chen Carter Yagemann Evan Downing

Converting malware into images followed by vision-based deep learning algorithms has shown superior threat detection efficacy compared with classical machine learning algorithms. When malware are visualized as images, visual-based interpretation schemes can also be applied to extract insights of why individual samples are classified as malicious... (read more)

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