Image-Based Malware Detection Using Deep Convolutional Autoencoder and Random Forest
Image-based analysis has been extensively used for malware classification by converting binary files into grayscale images to extract structural and behavioral patterns. However, common deep learning approaches generally suffer from problems such as non-interpretability, class imbalance, and computational overhead....