Fig. 11
From: Federated learning with enhanced cryptographic security for vehicular cyber-physical systems
Comparative performance analysis of federated learning techniques across key evaluation metrics—accuracy, precision, and recall. The proposed method (FedBuff + ECC) demonstrates significantly improved performance compared to traditional approaches such as output perturbation, objective perturbation, bit-choosing algorithms, and encryption-based resource allocation.
