GraphIDS

CAN bus intrusion detection over temporal CAN event streams. The live training path materializes raw CAN rows as PyG TemporalData, then trains temporal event models through the Ray-backed experiment runner.

Where to start

• Module responsibilities — one-page map of what every layer owns from experiment YAML through runtime execution.
• Config system — how an experiment YAML becomes a cache build, training run, or analysis job.
• Data architecture — raw rows, explicit representations, materialized views, and discovery/hypotheses.
• Decisions — the ADR log. Permanent verdicts on the tools and patterns that got adopted or rejected.
• API Reference — auto-generated from docstrings.

Source

• Repo: https://github.com/frenken-lab/graphids
• Runtime docs (this site): built from docs/.