Integrating AI-Powered Biometric Authentication for Digital Twin Identity Security
Keywords:
AI-powered biometric authentication, digital twin, identity securityAbstract
Digital twin technologies, which create virtual replicas of real items, have heightened the need for secure digital identity management. Digital twin applications in healthcare, manufacturing, and urban planning need user and entity identity security. Traditional authentication techniques are sometimes complicated and insecure. Face recognition, fingerprints, and voice patterns for AI-powered biometric authentication look promising. This strategy combines sophisticated machine learning models with biometric technology to increase digital twin ecosystem identity verification accuracy and robustness. This paper discusses AI-powered biometric authentication for identity security in digital twin applications, including merits, downsides, and future implications. Case studies demonstrate its real-world use, and AI and biometrics may be used to secure next-generation digital twin systems.
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