Neural authentication emerges as a revolutionary “fourth paradigm” of identity verification, moving beyond passwords, tokens, and conventional biometrics. By leveraging brainwave patterns captured through EEG technology, the approach offers a uniquely dynamic and conscious-dependent credential that is virtually impossible to replicate. This directly addresses critical failures in existing systems, where stolen credentials account for 77–88% of breaches, and deepfakes increasingly compromise biometric defenses. Neural authentication integrates naturally with Zero Trust architectures and immersive environments, offering continuous, frictionless verification. However, significant challenges remain, including physiological variability caused by fatigue, stress, and medication, as well as session-to-session inconsistency and hardware constraints requiring advanced signal processing and machine learning. A robust implementation demands layered architecture spanning signal acquisition, edge processing, secure cryptographic communication, and deep learning-based authentication engines.