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This paper explores behavioral biometrics, an emerging authentication method leveraging unique user behavior patterns for continuous security. This dynamic approach offers enhanced protection compared to traditional methods, yet significant challenges must be addressed. A key concern, examined herein, is accuracy; false positives and false negatives can undermine system effectiveness. User frustration arises from false positives, while false negatives create security vulnerabilities. The work emphasizes the need for careful system tuning and advanced machine learning to mitigate these errors. Data privacy and security are also paramount, given the sensitive, non-replaceable nature of the collected information. The paper highlights the importance of robust security measures, user transparency, and informed consent. Furthermore, it acknowledges that natural human behavioral variability, influenced by physical and environmental factors, can impact authentication accuracy, necessitating adaptive systems. In conclusion, addressing these technical and ethical challenges is crucial for realizing the full potential of behavioral biometrics.