AITH: A Post-Quantum Continuous Delegation Protocol for Human-AI Trust Establishment
Organizations: Faculty of Business Administration, University of Macau, Macao SAR, China
Abstract
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.
Figures & tables
| Property | TLS 1.3 | OAuth 2.0 | Macaroons | AITH v5.1 |
|---|---|---|---|---|
| For AI agents | No | No | No | Yes |
| Continuous delegation | No | Credential TTL | Caveats | Certificate |
| Boundary enforcement | No | Scope str. | Caveats | 6-check engine |
| Per-op crypto cost | Handshake | Credential verify | HMAC | None |
| Push revocation | No | No | No | Yes ( 1s) |
| Responsibility chain | No | No | No | 3-tier hash |
| AP2 | AIP | A-JWT | CA-MCPQ | AITH | |
|---|---|---|---|---|---|
| Scope | Payments | General | Enterprise | MCP ext. | General |
| Delegation | Mandates | Cap. credentials | Intent credentials | Session | Cont. cert. |
| Per-op signing | Yes | Yes | Yes | Yes | No |
| Boundary engine | No | No | No | No | 6-check |
| Push revocation | No | TTL | No | No | Yes ( 1s) |
| Resp. chain | No | Completion | No | No | 3-tier hash |
| Lemma | Property | Result | Steps |
|---|---|---|---|
| L1 | Certificate Unforgeability | Verified | 12 |
| L2 | Boundary Inviolability | Verified | 6 |
| L3 | Revocation Timeliness | Verified | 14 |
| L4 | Chain Integrity | Verified | 9 |
| L5 | Delegation Scope Separation | Verified | 8 |
| Metric | Value |
|---|---|
| Boundary check latency (mean) | 0.21 s |
| Boundary check latency (P99) | 0.36 s |
| Single-core throughput | 4,703,414 ops/sec |
| Projected 64-core throughput | 301M ops/sec |
| Certificate issuance | 0.011 ms |
| Chain append | 7.5 s |
| Outcome | Count | % | Interpretation |
|---|---|---|---|
| Allowed | 79,500 | 79.5% | Autonomous within bounds |
| Escalated | 6,100 | 6.1% | Human judgment required |
| Blocked | 14,400 | 14.4% | Boundary violation caught |
| Mechanism | Per-Op Latency | Throughput |
|---|---|---|
| AITH Boundary Check | 0.21 s | 4.7M ops/sec |
| Macaroon (HMAC) | 1–10 s | 100K–1M ops/sec |
| OAuth 2.0 (JWT/RSA) | 0.1–1 ms | 1K–10K ops/sec |
| ML-DSA per-op sign | 2 ms | 500 ops/sec |
| Rnd | Vulnerability | Severity | Layer | Resolution |
|---|---|---|---|---|
| R1 | Hardcoded lattice params | Medium | Parameter | Parameterized config |
| R1 | No ring justification | Low | Parameter | NTRU ring documented |
| R2 | Custom hash unanalyzed | High | Algorithm | Replaced: SHA-256 |
| R2 | Gaussian sampling bias | High | Algorithm | CDT sampling |
| R2 | Missing formal reduction | High | Algorithm | SIS reduction proven |
| R3 | Trust score manipulation | Critical | Protocol | ML-DSA pivot (v3) |
AI Agent Security
Artificial intelligence agent security studies attacks and safeguards for tool-using, persistent, and collaborative systems across digital and physical settings.
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