Formal Verification of Secrecy in Group Key Protocols Using Event-B
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Bibliographic record
Abstract
Group key security protocols play an important role in today’s communication systems. Their verification, however, remains a great challenge because of the dynamic characteristics of group key construction and distribution protocols. Security properties that are well defined in normal two-party protocols have different meanings and different interpretations in group key distribution protocols, specifically, secrecy properties, such as group secrecy, forward secrecy, backward secrecy, and key independence. In this paper, we present a method to verify forward secrecy properties for group-oriented protocols. The method is based on a correct semantical link between group key protocols and event-B models and also uses the refinement process in the B method to model and verify group and forward secrecy. We use an event-B first-order theorem proving system to provide invariant checking for these secrecy properties. We illustrate our approach on the Tree based Group Diffie-Hellman protocol as case study.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it