AITH: A Post-Quantum Continuous Delegation Protocol for Human-AI Trust Establishment

Computer Science > Cryptography and Security [Submitted on 9 Apr 2026] AITH: A Post-Quantum Continuous Delegation Protocol for Human-AI Trust Establishment Zhaoliang Chen The rapid deployment of AI agents acting autonomously on behalf of human principals has outpaced the development of cryptographic protocols for establishing, bounding, and revoking human-AI trust relationships. Existing frameworks (TLS, OAuth 2.0, Macaroons) assume deterministic software and cannot address probabilistic AI agents operating continuously within variable trust boundaries. We present AITH (AI Trust Handshake), a post-quantum continuous delegation protocol. AITH introduces: (1) a Continuous Delegation Certificate signed once with ML-DSA-87 (FIPS 204, NIST Level 5), replacing per-operation signing with sub-microsecond boundary checks at 4.7M ops/sec; (2) a six-check Boundary Engine enforcing hard constraints, rate limits, and escalation triggers with zero cryptographic overhead on the critical path; (3) a push-based Revocation Protocol propagating invalidation within one second. A three-tier SHA-256 Responsibility Chain provides tamper-evident audit logging. All five security theorems are machine-verified via Tamarin Prover under the Dolev-Yao model. We validate AITH through five rounds of multi-model adversarial auditing, resolving 12 vulnerabilities across four severity layers. Simulation of 100,000 operations shows 79.5% autonomous execution, 6.1% human escalation, and 14.4% blocked. Comments: 11 pages, 8 tables, 5 theorems (machine-verified via Tamarin Prover). Supplementary materials including formal verification model and reference implementation available from the author Subjects: Cryptography and Security (cs.CR); Artificial Intelligence (cs.AI) ACM classes: K.6.5; D.4.6; C.2.0 Cite as: arXiv:2604.07695 [cs.CR]   (or arXiv:2604.07695v1 [cs.CR] for this version)   https://doi.org/10.48550/arXiv.2604.07695 Focus to learn more Submission history From: Zhaoliang Chen [view email] [v1] Thu, 9 Apr 2026 01:30:28 UTC (12 KB) Access Paper: HTML (experimental) view license Current browse context: cs.CR < prev   |   next > new | recent | 2026-04 Change to browse by: cs cs.AI References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)