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Intrusion Detection System Performance Evaluation Anomaly Detection Method
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Abstract
MQTT is the dominant lightweight publish–subscribe protocol for IoT deployments, yet edge security remains inadequate. Cloud-based intrusion detection systems add latency that is unsuitable for real-time control, while CPU-bound firewalls and generic SDN controllers lack MQTT awareness to enforce session validation, topic-based authorization, and behavioral anomaly detection. We propose a P4-based data-plane enforcement scheme for protocol-aware MQTT security and anomaly detection at the network edge. The design combines parser-safe MQTT header extraction with session-order validation, byte-level topic-prefix authorization with per-client rate limiting and soft-cap enforcement, and lightweight anomaly detection based on KeepAlive and Remaining Length screening with clone-to-CPU diagnostics. The scheme leverages stateful primitives in BMv2 (registers, meters, direct counters) to enable runtime policy adaptation with minimal per-packet latency. Experiments on a Mininet/BMv2 testbed demonstrate high policy enforcement accuracy (99.8