Research simulation exploring how poisoning attacks corrupt federated learning aggregation
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Updated
May 25, 2026 - Python
Research simulation exploring how poisoning attacks corrupt federated learning aggregation
The repository focuses on conducting Federated Learning experiments using the Intel OpenFL framework with diverse machine learning models, utilizing image and tabular datasets, applicable different domains like medicine, banking etc.
Official implementation of "FedBand: Adaptive Federated Learning Under Strict Bandwidth Constraints"
Federated learning for wearable stress detection. Adds differential privacy, homomorphic encryption, and device authentication on top, so no one's raw data or their participation in the study ever leaves their device.
Privacy-preserving federated learning system combining ECG and clinical data for cardiac risk prediction — 98.05% accuracy via an interpretable meta-ensemble with reliability-based weighting.
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