TrustedARI:面向智能体AI的信任原生代理路由基础设施

TrustedARI: Towards Trust-Native Agentic Routing Infrastructure for Agentic AI

精选理由

这篇论文搞了个TrustedARI,让AI代理调用外部服务时能验证路由安全,还比现有方案省近四成带宽,部署不用改服务商代码。

AI 摘要

TrustedARI是首个为智能体AI设计的信任原生代理路由基础设施,解决传统ARI架构中代理查询和服务响应明文暴露、路由验证缺失的风险。其核心创新包括:三方可信握手协议(通信开销降低39.34%)、隐私保护查询构建协议(平均计算耗时0.19秒、通信成本0.58 MB)、可验证计费协议(证明生成加速28.20倍)。实验表明,TrustedARI无需修改服务提供商即可直接部署。该研究在arXiv上发表,为智能体路由安全提供了可落地方案。

原文 · arXiv cs.AI

TrustedARI: Towards Trust-Native Agentic Routing Infrastructure for Agentic AI

AI agents increasingly access external models, tools, and services through Agentic Routing Infrastructure (ARI) to manage the overhead of heterogeneous interfaces and fragmented subscriptions. Yet, the architecture of ARI introduces fundamental trust risks: it obtains plaintext access to agent queries and service responses, while leaving agents unable to verify that their queries are routed to intended service providers or that requests and responses remain untampered. To address this problem, we present TrustedARI, the first trust-native agentic routing infrastructure for agentic AI. Architecturally, TrustedARI is built upon three core innovations: (i) an ARI-adapted three-party TLS handshake that enables the agent and ARI to jointly authenticate the service provider through role-specific distribution of TLS key materials; (ii) a privacy-preserving query-construction protocol that allows the agent and ARI to collaboratively construct well-formed queries without exposing their respective private inputs; and (iii) a verifiable billing protocol that supports fair usage-based settlement while preserving the integrity and confidentiality of service responses. We implemented and extensively evaluated a prototype of TrustedARI to validate its performance. Experiments confirm that TrustedARI is highly efficient: our ARI-adapted handshake protocol reduces communication overhead by 39.34% compared to the existing three-party TLS handshake. Furthermore, the privacy-preserving query-construction protocol imposes negligible overhead-averaging 0.19 seconds in computation time and 0.58 MB in communication costs-while the verifiable billing protocol speeds up proof generation by 28.20x. Crucially, TrustedARI is readily deployable without any modification to the service providers.