Abstract: The malware attacks are increasing exponentially in our day-to-day lives. Detecting and classifying the malware into different categories and families is necessary to mitigate them.

Abstract: This study explores feature extraction and machine learning methods for automated sleep stage classification using physiological signals, focusing on PPG-derived parameters and skin ...