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Research Paper

MU-IoT - Comprehensive IoT Network Intrusion Dataset 2024

Cybersecurity
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Abstract

"New realistic IoT network intrusion dataset (MU-IoT) with comprehensive attack scenarios for cybersecurity research. Published in IEEE 2024 with 4+ citations. Covers multiple IoT protocols and device types."

Description

Introduction to MU-IoT Dataset

The MU-IoT dataset is a state-of-the-art cybersecurity resource published in IEEE 2024, specifically engineered to address gaps in existing IoT intrusion detection datasets. It provides realistic network traffic from diverse IoT devices under both normal operations and sophisticated attack scenarios.

Device Ecosystem

Traffic captured from diverse IoT device categories: smart home (IP cameras, smart locks, voice assistants, smart plugs), healthcare IoT (blood pressure monitors, glucose meters, pulse oximeters), wearables (fitness bands, smartwatches), environmental sensors (temperature/humidity, air quality monitors), industrial devices (PLCs, SCADA systems, industrial gateways), and network infrastructure (routers, switches, IoT hubs).

Protocol Coverage

Application layer protocols include MQTT, CoAP, HTTP/HTTPS, and AMQP. Network layer covers IPv4, IPv6, and 6LoWPAN. Link layer includes WiFi, Bluetooth LE, Zigbee, and Z-Wave. Cellular protocols include NB-IoT and LTE-M.

Attack Taxonomy

Includes network-layer attacks (DDoS, port scanning, spoofing), application-layer attacks (MQTT hijacking, CoAP exhaustion, HTTP exploits), IoT-specific attacks (firmware manipulation, replay attacks, sensor poisoning, botnet C&C traffic), and advanced persistent threats (multi-stage attacks, lateral movement, data exfiltration). Features precise binary and multi-class labels, temporal annotations, device-level labels, and manual verification by security experts.

View Data Structure

To explore column names, data types, and sample rows, visit the official dataset page on Research Paper.

Preview on Research Paper

Cite This Dataset 

Clinton, U. B., & others (2024). MU-IoT - Comprehensive IoT Network Intrusion Dataset 2024. IEEE Conference Proceedings. [Dataset]. Research Paper. https://doi.org/10.1109/XXX.2024.10747334

Source: Research Paper (2024) · DOI: 10.1109/XXX.2024.10747334

Indexed by IoTDataset.com on Jan 22, 2026

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Related Topics & Keywords

#IoT security #intrusion detection #network attacks #MQTT #CoAP #DDoS #botnet #IEEE #cybersecurity #machine learning

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