3 min readResearch note
Situational Awareness for Cyberdefense with Decentralized Federated Learning
Build cyberdefense situational awareness with DFL: provenance, coverage, uncertainty and shared context for operational decisions.
Research Notes on Federated Learning, Cybersecurity and Cyberdefense
Research notes and technical guides on federated learning, distributed AI, cyberdefense, trustworthy systems, and privacy-preserving platforms.
18 articles. Page 3 of 3.
3 min readResearch note
Drones, Edge Intelligence and DFL for Cyberdefense Operations
DFL for drones and edge systems: local inference, intermittent links, node recovery and evaluation of resources and reliability.
3 min readResearch note
Byzantine-Resilient Aggregation for Decentralized Federated Learning
Median, trimmed mean and trust in DFL: examples, local poisoning assumptions and defense costs with legitimate non-IID clients.
3 min readResearch note
Privacy-Preserving IoT Security with Decentralized Federated Learning
Privacy in IoT security with DFL: protected units, differential privacy budgets, secure aggregation and leakage-aware evaluation.
5 min readGuide
NEBULA: A Platform for Decentralized Federated Learning
NEBULA guide: architecture, official documentation and a reproducible protocol for evaluating DFL topology, privacy, attacks and resources.
6 min readGuide
Decentralized Federated Learning: Fundamentals and Applications
DFL foundations: peer aggregation, topology, convergence, privacy and communication. Learn when it fits better than server-based FL.