DBSCAN on flow features reaches NMI 0.78 with ground-truth IoT device labels on Deakin captures, while BIRCH supports 0.13-second incremental updates with 0.87 purity on a novel device.
IoTTFID: An incremental IoT device iden- tification model based on traffic fingerprint,
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Unsupervised Baseline Clustering and Incremental Adaptation for IoT Device Traffic Profiling
DBSCAN on flow features reaches NMI 0.78 with ground-truth IoT device labels on Deakin captures, while BIRCH supports 0.13-second incremental updates with 0.87 purity on a novel device.