This paper proposes a comprehensive reliability assessment framework for deepfake detectors, moving beyond traditional performance metrics. It evaluates five state-of-the-art methods across four crucial pillars: transferability, robustness, interpretability, and computational efficiency, revealing both progress and critical limitations in current detection technologies.

This survey comprehensively analyzes the growing cybersecurity challenges in Internet of Things (IoT) networks, examining vulnerabilities and threats across different layers. It also evaluates advanced defense mechanisms leveraging AI, Blockchain, and Zero Trust Architecture to enhance IoT ecosystem resilience.