About 4.6 million labelled bi-flows with 80 CICFlowMeter features, covering 15 attack families plus benign traffic in 16 single-class files. CC BY 4.0.
A 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.
Multimodal smart city dataset combining environmental sensors (temperature, humidity, gas, vibration, noise, motion) and surveillance images with binary anomaly labels. Designed for edge computing, urban anomaly detection, and real-time city monitoring research.
Multivariate dataset exploring the integration of IoT sensor data with AI algorithms across multiple domains. Features diverse sensor types, environmental parameters, and AI model performance metrics for hybrid intelligent systems research.
Dataset for evaluating federated learning approaches to IoT intrusion detection published in Nature Scientific Reports January 2026. Features distributed network traffic from multiple IoT deployments with privacy constraints and decentralized learning evaluation metrics.
State-of-the-art IIoT dataset from Canadian Institute for Cybersecurity with synchronized sensor and network data from 40 devices including 15+ industrial sensors. Features multi-objective feature selection for anomaly detection in industrial environments.
Comprehensive dataset capturing cybersecurity threats and sustainability metrics in smart city IoT and edge networks, including communication behavior, energy consumption patterns, and attack scenarios.
Dataset simulating IoT sensor data transmission across sensor, edge, and cloud computing layers. Contains 10,000+ records of transmission metrics, network performance, and latency measurements.
Simulated smart city environment capturing multimodal data from distributed urban sensors and surveillance sources. Includes synchronized environmental and visual data for edge computing and urban anomaly detection research.