Alembic - Automated Model Inference for Stateful Network Functions

Alembic - Automated Model Inference for Stateful Network Functions

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Use Symbolic Models to represent Large Sets

7 of 19

7 of 19

Use Symbolic Models to represent Large Sets

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Alembic - Automated Model Inference for Stateful Network Functions

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  1. 1 Intro
  2. 2 Motivating Example: Stateful Firewall (FW)
  3. 3 Today: Need NF Models for Testing and Verification
  4. 4 Limitation of Handwritten Model: Inaccuracy
  5. 5 Challenges on Large Configuration Space
  6. 6 We Can Compose Models of Individual Rules
  7. 7 Use Symbolic Models to represent Large Sets
  8. 8 Exploit Independence to Create an Ensemble of FSMS
  9. 9 Challenges on Inferring NF Behavior
  10. 10 Background on L* for Black-box FSM Inference
  11. 11 Practical Challenges of Applying L* for an NF
  12. 12 Generating Input Alphabet to handle Large Traffic Space
  13. 13 Learning the State Granularity
  14. 14 Alembic Workflow: Offline
  15. 15 Evaluation Summary
  16. 16 Evaluation Setup
  17. 17 Firewall Case Study: Untangle Firewall
  18. 18 Limitations and Future Work
  19. 19 Conclusions: Alembic can accurately model stateful NFS

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