Betrayal Detection

Betrayal detection research focuses on identifying deceptive or malicious behavior across diverse domains, from identifying manipulated audio and video to detecting anomalies in human movement and robotic actions. Current approaches leverage machine learning, employing techniques like transformer-based architectures for video analysis and stereo audio processing for deepfake detection, alongside reinforcement learning for modeling cooperative interactions and betrayal penalties. This research is significant for enhancing security in various applications, including cybersecurity, surveillance, and human-robot interaction, by improving the ability to identify and mitigate deceptive actions.