A confidence score is a numerical value that indicates the degree of certainty an authentication system has in its decision about a user's identity.
In behavioral biometric systems, confidence scores are calculated by comparing real-time user behavior patterns—such as typing rhythm, mouse movement, or other behavioral characteristics—against established baseline profiles. The closer the current behavior matches the stored behavioral template, the higher the confidence score. Conversely, significant deviations from normal patterns result in lower scores.
Confidence scoring enables more nuanced security decisions than simple pass/fail authentication. Rather than immediately blocking access when behavioral patterns show minor variations, systems can respond proportionally. For example, a confidence score of 85% might allow normal access, while a score of 60% could trigger additional authentication challenges, and a score below 30% might immediately lock the session.
This approach reduces false positives that could disrupt legitimate users while maintaining robust security against unauthorized access attempts. Organizations can customize confidence thresholds based on their specific risk tolerance and security requirements.
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