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Securing Autonomous AI Agents in Hybrid Enterprise Systems: A Behavior-Centric Trust Enforcement Architecture

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Behavior-aware enforcement mitigates risks linked to autonomous agent overreach and misalignment with system context.
Results show that the proposed architecture effectively enhances security beyond traditional identity-based mechanisms.
Four core components support the framework's operation: intent validation, trust graph, and integration memory.
Use cases evaluated include network configuration, backup compliance, and SaaS auditing to demonstrate effectiveness.

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Behavior-centric trust enforcement architecture governs AI interactions in hybrid environments, indicating enhanced security measures.

Muthukrishnan Manoharan (2025) studied this question.

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