Smart Home Intrusion Detection Dataset — 7 Attack Scenarios
Smart home traffic captured under normal operation and seven multi-stage attack scenarios across heterogeneous end devices. CC BY 4.0, published 2026.
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Smart home traffic captured under normal operation and seven multi-stage attack scenarios across heterogeneous end devices. CC BY 4.0, published 2026.
View DatasetAbout 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.
View DatasetLarge-scale distributed IoT IDS benchmark with traffic captured at individual device interfaces across 78 heterogeneous smart city IoT devices using the Gotham testbed. PCAP and CSV. Published January 2026 on Zenodo. Designed for federated learning and decentralised IDS research.
View DatasetLatest 2026 IoT malware dataset from the Canadian Institute for Cybersecurity (CIC) and Yunnan University, featuring comprehensive malware samples and behavioral analysis data for IoT threat detection research.
View DatasetA federated learning evaluation across several contemporary IoT and IIoT intrusion detection datasets, benchmarking algorithms such as FedAvg, FedProx, and FedNova with LSTM and Transformer models in in-domain, cross-dataset, and multi-dataset federation scenarios.
View DatasetWearable IMU dataset from 22 Parkinson's disease patients performing standardized motor tasks, with four inertial sensors (ankles, wrist, lower back) capturing freezing of gait (FoG) episodes, designed for algorithm development and clinical gait analysis.
View DatasetMultimodal dataset from 18 subjects with wearable IMUs (wrists, torso), Bluetooth indoor localization, and first-person video capturing 12 activity categories in realistic home/office scenarios for human activity recognition and fall detection research.
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