Could AI/ML be used to evaluate authentication trustworthiness?
Yes. Mailbox providers already use machine learning to evaluate sender reputation and authentication patterns.
AI can detect:
- forged DKIM signatures
- suspicious alignment behavior
- inconsistent SPF usage
- anomalies in ARC chains
- predictive indicators of domain abuse
In the future AI may correlate authentication events with behavioral signals to build more adaptive trust scoring. This includes sorting senders into reputation cohorts or behavioral clusters in real time instead of relying on simple pass fail signals.
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