MQTT_UAD: MQTT Under Attack Dataset for Detection of Attacks in IoT Networks Using MQTT Protocol
Abstract
"MQTT_UAD is a public MQTT traffic dataset published in Data in Brief 2025, containing labeled benign and attack scenarios in IoT networks that use the MQTT protocol, designed for training and evaluating intrusion detection systems."
Description
Overview
MQTT_UAD (MQTT Under Attack Dataset) is a public dataset of MQTT traffic for detecting cyberattacks in IoT networks that use the MQTT protocol. It is introduced in a 2025 Data in Brief article and released together with structured data suitable for machine learning-based intrusion detection.
Scope and Design
- Focuses specifically on MQTT-based IoT communication, a widely used publish/subscribe protocol in constrained IoT environments.
- Includes benign traffic as well as multiple attack scenarios against MQTT infrastructure, enabling comparative evaluation of intrusion detection techniques.
- Provides labeled records so that supervised learning methods can distinguish between normal and malicious activity.
Intended Uses
- Training and benchmarking intrusion detection systems for MQTT-based IoT deployments.
- Developing and comparing feature-engineering strategies and classifiers tailored to MQTT traffic.
- Supporting research on lightweight IDS models that can operate on resource-constrained IoT gateways.
Access and License
The dataset is described in the Data in Brief article and distributed via the publisher's data platform and an associated external repository. Users should follow the citation and licensing guidance provided in the article and dataset page.
📊 View Data Structure
To explore column names, data types, and sample rows, visit the official dataset page on Kaggle.
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Cite This Dataset
Aveleira-Mata, J. (2025). MQTT_UAD: MQTT Under Attack Dataset for Detection of Attacks in IoT Networks Using MQTT Protocol. Data in Brief. [Dataset]. Elsevier. https://www.sciencedirect.com/science/article/pii/S2352340925008881
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Original source: Elsevier (2025). Visit official page for more details.
Indexed by IoTDataset.com on Feb 03, 2026
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