🤖 AI Summary
This work addresses the lack of a unified trust visibility mechanism in cross-vendor AI agent tooling, which can lead to cascading failures when compromised tools are repeatedly invoked. To mitigate this, the paper proposes AgentToolMO, a framework grounded in the 3GPP NRM information model that integrates a formal trust state machine and a bounded-convergence damped cascade propagation mechanism. Trust states across vendors are disseminated in near real time and their impacts traced via standardized MnS interfaces. Experimental results demonstrate that the approach reduces failure response latency from hours to near real time, guarantees cascade convergence within a finite number of iterations, and incurs sublinear notification overhead, thereby significantly enhancing system resilience and interoperability.
📝 Abstract
Autonomous Network Levels 4-5 require AI agents to invoke tools across vendor boundaries without human oversight, yet existing management standards lack a standardized mechanism for cross-vendor trust visibility. When a tool from Vendor B is compromised, agents from Vendor A continue invoking it -- unaware of the trust degradation -- causing cascading service impact. We present AgentToolMO, a proposed 3GPP NRM information model for agent tool trust management. The model comprises: a formally defined trust state machine with provable graduated enforcement, damped cascade propagation with bounded convergence, cross-vendor trust notifications via existing Management Services (MnS) interfaces, and retroactive impact assessment through NRM dependency graph traversal. Simulation-based evaluation across multi-vendor topologies shows that standardized cross-vendor notifications reduce blast radius from hours-scale undetected propagation to near-real-time containment bounded by MnS notification delivery, with cascade convergence guaranteed in bounded iterations and sub-linear notification scaling across vendor domains. The framework operates within existing 3GPP management infrastructure, leverages existing protocols, and provides a standardization pathway for trustworthy multi-vendor autonomous network management.