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.
12 articles. Page 1 of 2.
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.
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 readResearch note
D-MoE: Distributed Mixture of Experts for Edge LLMs
Distributed MoE at the edge: expert placement, critical-path latency, bandwidth, activations and failure recovery.
5 min readResearch note
Modalis: Prototype Exchange for Heterogeneous Multimodal DFL
How Modalis works: multimodal prototypes, gating and alignment in DFL. Published results, limitations and proposed ablations.