CLAD is a clustered federated learning framework with a dual-mode architecture for joint anomaly detection and attack classification in IoT using labeled and unlabeled data.
Detect- ing V olumetric Attacks on loT Devices via SDN-Based Monitoring of MUD Activity,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
CLAD: A Clustered Label-Agnostic Federated Learning Framework for Joint Anomaly Detection and Attack Classification
CLAD is a clustered federated learning framework with a dual-mode architecture for joint anomaly detection and attack classification in IoT using labeled and unlabeled data.