Industrial IoT IDS dataset with labelled TCP/IP and DNP3 flow statistics plus PCAP files for 9 SCADA cyberattacks. CSV and PCAP formats for ML/DL IDS research.
Agricultural IoT network intrusion dataset with 1.31 million labeled flow records (532 MB) emulating a real AG-IoT farm environment. Covers crop health, weather, and soil condition data with network attack scenarios. CSV via Zenodo. Used for smart farming security research.
Large-scale IoT cybersecurity dataset with 47M+ labeled network flows from 105 real IoT devices across 33 attack types in 7 categories. PCAP and CSV formats. Built for IDS/IPS development and ML-based IoT traffic classification research.
Heterogeneous IoT/IIoT dataset from UNSW Canberra Cyber Range with network traffic, Windows/Linux OS traces, and IoT sensor telemetry. Labeled for 9 attack types including DoS, DDoS, ransomware, and XSS. CSV and PCAP formats. Benchmark for AI-based IDS evaluation.
Real IoT malware traffic dataset with 325M labeled network flows from 20 malware and 3 benign device captures over 500+ hours. PCAP and Zeek conn.log formats. Used for IoT botnet detection, malware traffic classification, and ML security research.
Real-time IoT network security dataset from a live IoT infrastructure with 41 bidirectional flow features. Includes ThingSpeak-LED, Wipro-Bulb, and MQTT-Temp devices with SSH brute force, DDoS (Hping/Slowloris), and Nmap attack scenarios. CSV format. Used for adaptive IDS development.
Realistic IoT/IIoT cybersecurity dataset supporting centralized and federated learning with 15 attack types across network, application, and protocol layers. CSV and PCAP formats (~12 GB). Available via IEEE Dataport and Kaggle. Designed for edge computing IDS research.
Reproducible large-scale IoT network dataset from 78 emulated devices using MQTT, CoAP, and RTSP protocols. Includes benign and malicious traffic with DoS, brute force, scanning, and C&C attacks in PCAP and CSV formats.