Malware classification project using static analysis, where applications are converted into bytecode, the byte sequences are transformed into grayscale images, and deep learning–based image classification is applied to categorize malware into 31 distinct subclasses for accurate detection without executing the files.
machine-learning deep-learning tensorflow cybersecurity malware-detection malware-classification static-malware-analysis efficientnetv2 security-ml image-based-malware
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Updated
Feb 18, 2026 - Jupyter Notebook