4 min readResearch note
Autonomous Cyberdefense Needs More Than an LLM
Autonomous cyberdefense with LLMs: control states, action boundaries, recovery and separate evaluation of utility and safety.
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.
Topic: Trustworthy AI Clear topic
6 articles. Page 1 of 1.
5 min readResearch note
How to Measure Robustness in Adversarial DFL Experiments
Evaluate DFL robustness with F1, false rejection, overhead and recovery. Interpret Flighter and compare clean and attacked conditions.
5 min readResearch note
From Monitoring to Mitigation: A DFL Cyberdefense Lifecycle with LLM Explanations
Connect telemetry, federated learning, alerts and LLM-assisted mitigation with traceable evidence, validation and reviewed feedback.
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.
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.
3 min readResearch note
Federated Energy Anomaly Detection for Critical Infrastructure
Federated energy anomaly detection: temporal splits, false alerts, drift and operational evidence for critical infrastructure.