The BCCC-IoT-IDS-ZWave-2025 Dataset is a large-scale, multi-source IoT security dataset developed over five months (20 TB data, including more than 1 BILLION records) using a comprehensive smart-home testbed comprising more than 110 devices, including sensors, actuators, smart plugs, locks, meters, and controllers. According to the paper, the dataset includes 88 distinct attack scenarios spanning network-layer, device-layer, and service-layer threats, making it the most extensive Z-Wave–focused dataset to date. The dataset integrates five data sources: IP-based traffic, Z-Wave protocol communication data, device activity logs, MQTT traffic, and MQTT message logs, providing a holistic view of benign and malicious behavior. It contains multi-class records covering 81 IP network traffic classes and 24 Z-Wave classes, supporting advanced behavioral profiling and classification tasks. The complete dataset, including raw packets, CSV records, metadata, and labeling files, is publicly available and represents a significant resource for intrusion detection, device fingerprinting, and IoT threat analysis.
The full research paper outlining the details of the dataset and its underlying principles:
"Toward generating a large-scale IoT-Zwave intrusion detection dataset: Smart device profiling, intruders behavior, and traffic characterization”, Mohammad Moein Shafi and Arash Habibi Lashkari, Internet of Things, Volume 34, November 2025, https://doi.org/10.1016/j.iot.2025.101747
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