RT-IoT2022 - Real-Time IoT Network Security Dataset
Comprehensive real-time IoT infrastructure dataset from UCI. Captures bidirectional network traffic using Zeek monitoring tool. Ideal for IDS development.
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Comprehensive real-time IoT infrastructure dataset from UCI. Captures bidirectional network traffic using Zeek monitoring tool. Ideal for IDS development.
View Dataset1,191,264 network intrusion instances with 47 features. Large-scale dataset for training predictive models to detect IoT network attacks and anomalies.
View DatasetIoT-based environmental perception data studying impact on university students' mental health. Integrates temperature, humidity, noise, and air quality sensors.
View DatasetIndustry-standard dataset for prognostics research with simulated run-to-failure data from 100 turbofan engines including 21 sensor readings and remaining useful life (RUL) labels for predictive maintenance algorithms.
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 DatasetRealistic network traffic data containing benign activities and common IoT-targeted attacks like Brute Force, DoS, and Infiltration.
View DatasetHigh-fidelity biometric signals from wearable IoT nodes, including multi-lead ECG and 3-axis motion data for remote healthcare applications.
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 DatasetReal-time IoT sensor data from wearable health monitoring devices tracking patient vital signs including body temperature, blood pressure (systolic/diastolic), heart rate, and device battery levels for remote healthcare monitoring and predictive analytics.
View DatasetReal-time IoT sensor data collected from industrial machines for predictive maintenance and anomaly detection in smart manufacturing environments, featuring temperature, vibration, pressure readings, and machine operational status for Industry 4.0 applications.
View DatasetSimulated sensor data from IoT-based wearable healthcare devices monitoring vital signs including temperature, blood pressure, heart rate, and device battery levels for real-time remote patient monitoring and health analytics applications.
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