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Malware Image Classification Using Machine Learning With Local Binary Pattern, Jhu-Sin Luo, Dan Lo
Malware Image Classification Using Machine Learning With Local Binary Pattern, Jhu-Sin Luo, Dan Lo
Master of Science in Computer Science Theses
Malware classification is a critical part in the cybersecurity.
Traditional methodologies for the malware classification
typically use static analysis and dynamic analysis to identify malware.
In this paper, a malware classification methodology based
on its binary image and extracting local binary pattern (LBP)
features are proposed. First, malware images are reorganized into
3 by 3 grids which is mainly used to extract LBP feature. Second,
the LBP is implemented on the malware images to extract features
in that it is useful in pattern or texture classification. Finally,
Tensorflow, a library for machine learning, is applied to classify
malware images with …