Author

Ahmed Hamed

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Open access Jul 2026

Hybrid noise-resistant technique for malware classification.

This study proposes a novel hybrid malware representation framework that integrates Convolutional Autoencoder (CAE)-based latent structural learning with Local Binary Pattern (LBP)-based texture feature extraction for robust malware classification and represents one of the first comprehensive investigations of hybrid latent-texture representation learning within a memory-forensics malware visualization setting.

Syed Shakir Hameed Shah, Syed Shakir Hameed Shah, Ahmed Hamed et al. · Scientific Reports · 0 citations