Non-contact authentication for key recovery and platform security provisioning

Abstract

Secure AI authentication is implemented for selectable environments with a selectable combination of ML models processing selectable input credentials, e.g., biometric and/or non-biometric credentials, such as a key associated with a secure model, user location information, a user gesture credential, and/or a user movement pattern credential. ML models may be selectively applied in serial or parallel in a selected authorization procedure. ML model applicability may vary based on one or more parameters, such as time of day, or one or more detected input credentials, such as user gestures, secure model keys, or biometric voice or face recognition. For example, AI authorization (e.g., for biometric credentials) augmented with an ultra-wideband (UWB) communication protocol provides robust user authentication via a native cryptographic exchange and accurate user location credentials for proximity and geo-fenced confirmation of other user credentials, such as biometric credentials, thereby preventing false positives by spoofing.