4 min readGuide
Privacy, Secure Aggregation and Robustness in DFL
Combine differential privacy, secure aggregation and robust DFL with explicit trust assumptions, local threat budgets and joint evaluation.
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
7 articles. Page 1 of 2.
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
LLM-Supported Attack Mitigation Without Unsafe Autopilot
LLM-assisted mitigation: playbooks, evidence, permissions, idempotency and recovery. Turn recommendations into verifiable actions.
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.
3 min readGuide
Golden Sets for LLM Evaluation: Small, Curated and Difficult to Cheat
Build golden sets for LLMs and RAG with examples, adjudication, leakage-aware splits and bilingual security cases.
3 min readGuide
Metrics for LLMs, RAG and Cybersecurity Systems
LLM and RAG metrics: retrieval recall, citations, unsafe actions, calibration, latency and uncertainty. Define fair comparisons.