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This paper introduces the Guard Rail Validation (GRV) framework, designed to intercept and validate AI-driven decisions in autonomous telecom networks before they affect live operations. By evaluating decisions across multiple dimensions such as action scope and service criticality, the framework applies graduated validation mechanisms tailored to the assessed criticality level. The evaluation demonstrates that GRV significantly enhances threat coverage against known AI/ML attacks, thereby reducing the risk of erroneous autonomous decisions in critical network environments.
A novel validation framework that ensures AI agents in telecom networks make safer, more reliable decisions by dynamically assessing the criticality of their actions.
The evolution toward fully autonomous telecommunications networks (Autonomous Network Levels 4-5) requires AI/ML agents to make real-time network decisions without human intervention. However, no standardized runtime mechanism exists to intercept and validate individual inference outputs before they trigger live network state changes, creating risks of erroneous autonomous decisions. This paper proposes the Guard Rail Validation (GRV) framework, a standardizable runtime architecture for intercepting and validating AI-driven decisions before execution. The framework evaluates decisions across multiple weighted dimensions -- including action scope, action type, service criticality, agent autonomy level, reversibility, and temporal behavioural patterns -- to determine a criticality level. Based on this level, graduated validation mechanisms are applied: execute-with-logging, bounds checking, independent agent validation, or multi-agent consensus. The framework additionally provides cross-agent conflict detection with criticality-weighted priority resolution and runtime conformance logging for regulatory compliance (e.g., EU AI Act Article 14). We present the architecture, algorithmic procedures, O-RAN deployment model, and evaluate threat coverage against known AI/ML attacks in telecommunications.
