What question did this study set out to answer?

The central aim is to enhance automated incident response in IoT environments using multiple intrusion detection systems.

April 14, 20260 citationsOpen Access

IoTEdu Core: Automated Intrusion Detection and Response in IoT Environments through Multi-IDS Orchestration

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JAJoner Assolin MCMatheus Martins CioccaUniversidade Federal do Pampa ECEmanuel CarricioUniversidade Federal do Pampa

Key Points

The central aim is to enhance automated incident response in IoT environments using multiple intrusion detection systems.
Implemented multi-IDS orchestration with Suricata, Snort, and Zeek.
Conducted 75 runs across five different attack types.
Measured average containment time and latency during detection.
Achieved an average containment time of 5.56 seconds.
Identified latency issues primarily due to detection processes.
Revealed a trade-off between speed of signature-based methods and the contextual awareness of behavior-based approaches.

Abstract

IoT environments increase the attack surface and challenge incident response. IoTEdu orchestrates multiple IDSs (Suricata, Snort, Zeek) in a unified pipeline with event correlation and automated blocking. Across five attack types (75 runs), it achieves 5.56s average containment, with latency dominated by detection. Results expose a trade-off between signature-based speed and behavior-based context, showing that multi-IDS orchestration improves automated response in dynamic IoT settings.

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IoTEdu Core: Automated Intrusion Detection and Response in IoT Environments through Multi-IDS Orchestration

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