Securing Federated Learning Against Extreme Model Poisoning Attacks via Multidimensional Time Series Anomaly Detection on Local UpdatesJan 1, 2025·Last updated on Jan 1, 2025Computational Modeling;Servers;Data Models;Training;Standards;Time Series Analysis;Predictive Models;Anomaly Detection;Security;Federated Learning;Federated Learning;robustness;model Poisoning Attacks;deep Learning;anomaly Detection;security ← On the legal implications of Large Language Model answers: A prompt engineering approach and a view beyond by exploiting Knowledge Graphs Jan 1, 2025Additive Counterfactuals for Explaining Link Predictions on Knowledge Graphs Nov 25, 2024 →