MQTT-IoT-IDS2020 — MQTT Internet of Things IDS Dataset
MQTT IoT IDS dataset from a simulated network with 12 sensors, broker, camera, and attacker. PCAP and CSV features support MQTT intrusion detection research.
View DatasetShowing 11 of 11 datasets
MQTT IoT IDS dataset from a simulated network with 12 sensors, broker, camera, and attacker. PCAP and CSV features support MQTT intrusion detection research.
View DatasetIoT IDS dataset for distinguishing normal and malicious ICMP/Ping traffic generated from an ESP-01s embedded device. PCAP, Zeek logs, and labelled CSV files.
View DatasetA comprehensive dataset derived from real-time IoT infrastructure, designed for intrusion detection research and network security analysis.
View DatasetComprehensive synthetic dataset designed for analyzing DDoS attacks in Internet of Things environments.
View DatasetA large-scale, reproducible network dataset for evaluating modern IoT intrusion detection systems.
View DatasetComprehensive large-scale IoT intrusion detection dataset from Canadian Institute for Cybersecurity with 33 attack types across 105 real IoT devices. Includes 8.94 GB of network traffic data covering DDoS, DoS, Mirai, MITM, and reconnaissance attacks.
View DatasetComprehensive network traffic dataset from UNSW Canberra Cyber Range Lab capturing benign and malicious flows in simulated IoT/IIoT smart environments using Argus and Zeek (Bro) tools.
View DatasetLarge-scale labeled network traffic captures (PCAPs) from IoT devices. Based on Stratosphere Laboratory's famous IoT-23 dataset with botnet and normal traffic patterns.
View DatasetThe most cited cybersecurity dataset worldwide with 2.8+ million network flows capturing 14 types of realistic attack scenarios including DDoS, brute force, botnet, and web attacks alongside benign traffic for advanced intrusion detection systems.
View DatasetComprehensive IoT network traffic dataset from an academic environment with 202,085 labeled records capturing benign and malicious activities for cybersecurity and anomaly detection research.
View DatasetReal-time physiological and network-level data from a secure IoT healthcare monitoring system tracking 2000 patients, including biometric readings (heart rate, temperature, blood pressure) and network metadata for anomaly detection and cybersecurity analysis.
View Dataset