IoT devices stop trusting a one-time credential: behavioral fingerprints plus federated learning cut membership inference success from 48.2% to 12.4%
IoT device authentication is shifting from a one-time check of fixed credentials to continuous checking of device behavior. Static credentials and centralized trust miss anomalies after a device is compromised and keep exposing identifiable attributes. A combined scheme uses hardware behavioral fingerprints, federated learning with differential privacy, a lightweight permissioned chain and agentic orchestration; on 11 Raspberry Pi devices in the PP-IDE dataset, differential privacy lowered membership inference attack success from 48.2% to 12.4%, with 99.2% authentication accuracy.