Authentication Scheme

Authentication schemes are evolving beyond traditional methods like passwords to address increasing security threats and the need for continuous verification. Current research heavily utilizes machine and deep learning, employing models such as convolutional neural networks, recurrent neural networks, and various classifiers (e.g., Random Forest, SVM) to analyze diverse biometric data including mouse dynamics, touch behavior, phone movement, and even environmental factors like underwater acoustic channel characteristics. This shift towards behavioral biometrics and AI-driven approaches aims to enhance security for various applications, from mobile devices to underwater communication networks, by providing more robust and context-aware authentication mechanisms.