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Systems and methods for continuous biometric authentication

專利號(hào)
US10867021B1
公開日期
2020-12-15
申請(qǐng)人
United Services Automobile Association (USAA)(US TX San Antonio)
發(fā)明人
John Shelton; Michael Wayne Lester; Debra Randall Casillas; Sudarshan Rangarajan; Maland Keith Mortensen
IPC分類
G06F7/04; G06F15/16; H04L29/06; G06F21/32; G10L17/24
技術(shù)領(lǐng)域
user,confidence,biometric,module,may,or,level,user's,voice,be
地域: TX TX San Antonio

摘要

Methods and systems for authenticating a user are described. In some embodiments, a series of voice interactions are received from a user during a voiceline session. Each of the voice interactions in the series of voice interaction may be analyzed as each of the voice interactions are received. A confidence level in a verification of an identity of the user may be determined based on the analysis of each of the voice interactions. An access level for the user may be automatically updated based on the confidence level of the verification of the identity of the user after each of the voice interactions is received.

說明書

The confidence level can include results from only the current sample or the confidence level can be inclusive of the entire series of interactions in the session up to the current interaction in the session (e.g., averaged). When computing the confidence level using the latter method, if the combined confidence from the first several interactions in the series is low (e.g., 2 on a scale of 1-10), then the verification must score a high confidence level in the next several interactions for the user to receive access to view any information or to participate in any activities. In some embodiments, the interactions may be weighted such that some interactions are more influential on the overall confidence level. For example, an analysis of the user speaking the user's member number may be given more weight than an analysis of the user stating the general purpose of the call since the user has likely stated the user's member number during previous interactions, resulting in a more accurate voice analysis. The various weightings may vary by industry, business, organization, user, or business unit.

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