为人工智能代理设计了可持续信任的后量子认证协议
AITH: A Post-Quantum Continuous Delegation Protocol for Human-AI Trust Establishment
- 用一次签名替代频繁签发,每秒可处理470万次边界检查
- 实现99.5%操作自主执行,6.1%需人工介入,14.4%被拦截
- 支持毫秒级撤销,适用于高安全需求的智能系统
AI代理在人类委托下自主运行的速度已超过可信关系建立、限定与撤销的密码协议发展。现有框架(如TLS、OAuth 2.0、Macaroons)假设确定性软件,无法应对连续运行且信任边界动态变化的概率型AI代理。本文提出AITH(AI信任握手)——一种后量子持续委托协议。AITH引入:(1) 使用ML-DSA-87(FIPS 204,NIST Level 5)一次性签署的持续委托证书,将每操作签发替换为每秒470万次的亚微秒级边界检查;(2) 六重检查的边界引擎,在关键路径上零加密开销地强制执行硬约束、速率限制与升级触发;(3) 推送式撤销协议,可在一秒内完成失效传播。三级SHA-256责任链提供防篡改审计日志。所有五个安全定理均通过Tamarin Prover在Dolev-Yao模型下机器验证。经五轮多模型对抗审计,修复了四个严重等级下的12个漏洞。模拟10万次操作显示:79.5%操作自动执行,6.1%需人工介入,14.4%被阻止。
原文摘要 · Abstract (English)
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.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品;中文卡片由大模型生成,请以原文为准。