Fingerprint, face, and iris recognition biometric technologies are increasingly applied in systems used for identity and access management (IAM). Another sophisticated technique, behavioral biometrics, infers recognition from dynamics of keyboard typing, movements of a mouse, and even walking. This paper addresses the opportunities and challenges of security, usability, and privacy in biometric as well as behavioral authentication. It assesses the dangers of spoofing, the risks of adversarial machine-learning assaults, and the potential privacy implications of storing biometric data. The comparison shows that while biometric systems improve ease of use, they are burdened by legal and moral issues, and while behavioral biometrics offer dynamic, situationally appropriate defense, they have low accuracy. The case studies illustrate the use of systems in finance, mobile technology, and essential facilities. The research found that integrating biometric and behavioral elements within multi-factor authentication (MFA) frameworks provides the marriage of resilience and user-friendliness while preserving privacy.