Synthetic IIoT Network Traffic Dataset โ 21% Attacks
Free CC0 synthetic dataset: 4,000 rows of Modbus, OPC UA and DNP3 flows labelled for SCADA intrusion detection. 21% Attacks. Reproducible from its seed.
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Free CC0 synthetic dataset: 4,000 rows of Modbus, OPC UA and DNP3 flows labelled for SCADA intrusion detection. 21% Attacks. Reproducible from its seed.
View DatasetFree CC0 synthetic dataset: 10,000 rows of Modbus, OPC UA and DNP3 flows labelled for SCADA intrusion detection. 29% Attacks. Reproducible from its seed.
View DatasetA high-resolution, three-year dataset from a real office building, integrating whole-building/end-use energy consumption, HVAC system data, environmental parameters, and ground-truth occupant counts. Essential for research in smart building energy prediction, optimization, and occupancy analytics.
View DatasetOpen-source GitHub repository featuring curated collection of 25+ datasets for deep learning applications in IoT including Gas Sensor Array Drift, ISOLET, Sleep-EDF, and comprehensive benchmark datasets under MIT license for unrestricted research use.
View DatasetA real-world cybersecurity dataset capturing MQTT-based IoT network traffic with live attacks and anomalous behavior. Collected from an active deployment with multiple attack types including DoS, SlowITe, and malformed injections. Provides both raw and preprocessed CSV files with rich metadata for intrusion detection and anomaly classification research.
View DatasetA dataset capturing real-time metrics of resource allocation and workload distribution across multi-tier IoT architectures. Includes latency, CPU and memory usage, task execution times, and predictive performance variables, enabling research in IoT resource management, edge analytics and performance optimization.
View DatasetA longitudinal visual dataset of urban streetlight scenes captured daily over several years including 2025, accompanied by structured metadata for smart city monitoring, drift detection, and anomaly analysis. Includes over 526,000 images with timestamps and GPS metadata, enabling vision-based model training in urban environments.
View DatasetZigBeeNet is a novel smart home IoT dataset containing decrypted network traffic from 15 Zigbee devices, including smart lights and motion sensors, collected over a 20-day period. It provides rare access to decrypted payloads and network characteristics, making it ideal for researchers focused on traffic modeling, device behavior analysis, and the development of high-fidelity Zigbee traffic generators.
View DatasetMQTT_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.
View DatasetDataSense is a real-time Industrial IoT (IIoT) dataset from the Canadian Institute for Cybersecurity, combining synchronized sensor and network data from a 40-device testbed with over 15 types of industrial sensors for anomaly and intrusion detection research.
View DatasetA synthetic but carefully constructed IoT dataset for smart home renewable energy management, providing five CSV datasets (20, 50, 100, 200 homes over 365 days) with daily energy consumption and production values to simulate small, medium, and large-scale smart city and smart home scenarios.
View DatasetA federated learning evaluation across several contemporary IoT and IIoT intrusion detection datasets, benchmarking algorithms such as FedAvg, FedProx, and FedNova with LSTM and Transformer models in in-domain, cross-dataset, and multi-dataset federation scenarios.
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