5 min readResearch note
Robust Decentralized Federated Learning: Limits and Open Questions
Open questions in robust DFL: dynamic graphs, manipulated context, privacy, missing modalities and experiments to test the limits.
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.
16 articles. Page 1 of 3.
4 min readGuide
Large Language Models for Cybersecurity: A Careful Starting Point
LLMs for cybersecurity: SOC use cases, evidence, permissions and evaluation. Move from summarization to a tool-using assistant.
4 min readGuide
Retrieval-Augmented Generation for Cybersecurity Workflows
RAG for cybersecurity: hybrid retrieval, current sources, permissions and evaluation. Diagnose retrieval and generation failures.
4 min readResearch note
GraphRAG for Cyber Threat Intelligence
GraphRAG for threat intelligence: entities, relationships, STIX, provenance and evaluation against passage-based retrieval.
3 min readResearch note
Parametric RAG: Moving Security Knowledge Into the Model
P-RAG versus contextual RAG: parametric memory, updates, permissions and provenance for cybersecurity knowledge.
3 min readGuide
Mixture of Experts in LLMs: Capacity Through Selective Routing
How MoE LLMs work: routing, active parameters, memory, load balance and latency and quality evaluation across languages.