Ahmed Aljughaiman

Anomaly detection of internet of medical things cyberattacks using federated learning

Abstract Devices connected to the Internet of Medical Things (IoMT) handle sensitive patient data under strict privacy and resource constraints. Centralized intrusion detection introduces privacy risks and communication bottlenecks, while existing Federated Learning (FL) solution...

Texture attention-guided adaptive LSB steganography with U-Net model and optional GA tuning integrated with ablation study

Image steganography involves hiding a secret image within a digital cover image, which remains invisible to ordinary viewers. The majority of current steganographic methods face an essential trade-off because higher Payload Capacity (PC) results in decreased visual undetectabilit...

An ensemble machine learning framework for accurate ransomware detection and family classification using LightGBM and random forest

Abstract Ransomware is a critical cybersecurity threat that leverages advanced encryption techniques to compromise individuals, organizations, and even national infrastructure. Ransomware incidents have increased exponentially in the past 5 years, with recent studies indicating t...