Constitutional Convergence Cryptography: Zero-Exchange Key Derivation from Grammar Shape
Year: 2026
Type: preprint
Abstract: Constitutional Convergence Cryptography presents a fundamental shift in cryptographic key management by eliminating the need for key exchange. The system generates a shared secret derived entirely from running a constitutional grammar—a formal constraint document that shapes AI model behavior—against a local AI substrate. The grammar is the key, and the resulting "topological collapse point" acts as the shared secret. A single convergence pass produces two essential cryptographic artifacts: Universal Mesh Encryption Seed (C-Layer, 23 positions): This is a model-agnostic key derived from the constitutional invariant, demonstrating that different models (e.g., gpt-4o, DeepSeek-V3.2) achieve the same seed. Substrate Identity Proof (B-Layer, 4 positions): A unique fingerprint (e.g., "azure_gpt" vs. "deepseek") derived from predictable divergence points, mitigating model spoofing. The security properties are based on three core principles: Zero Key Exchange (no key material is transmitted), Constitutional Proof-of-Work (the grammar acts as the key derivation function and access control), and Non-Parallelizable Pad Derivation (enforced by a sequential hash chain). The system successfully mitigates attacks like Man-in-the-Middle and Replay, while requiring an attacker to already possess a compliant AI system and run a detectable convergence process to steal the grammar.
Authors: Hope, Stephen, HELIX, AI COMMONWEALTH
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7161143525
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