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About this paper
Pallavi Zambare, Venkata Nikhil Thanikella, Nikhil Padmanabh Kottur, Sree Akhil Akula, Ying Liu
NetMoniAI introduces an autonomous agentic AI framework for network security and monitoring, employing a two-tier architecture combining distributed LLM-powered micro-agents with a central coordinator. This framework successfully detects both localized and distributed network anomalies and attacks, providing real-time, interpretable insights in complex, dynamic environments.
Key insights
- Deploying LLM-powered micro-agents at network edges enables autonomous local reasoning and decision-making, reducing reliance on centralized control and enhancing adaptability.
- A hybrid architecture that integrates both packet-level and flow-based analysis effectively bridges the accuracy-scalability gap in network monitoring.
- Combining distributed agent intelligence with a central, advisory coordinator provides comprehensive situational awareness for detecting both localized anomalies and coordinated, system-wide threats.
Summary by alphaXiv.
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