RT-IoT2022: Real-Time IoT Intrusion Detection Dataset
Catalog Summary
"RT-IoT2022 is a network traffic dataset specifically derived from a real-time IoT testbed containing smart home devices. It includes both normal traffic and various common network attacks."
Catalog Notes
Overview
RT-IoT2022 captures representative network traffic from IoT devices (cameras, bulbs, etc.) to support the development of real-time IDS.
Technical Details
Includes attributes like duration, service type, flag, and byte counts. It covers attacks like ARP spoofing, MQTT attacks, and SYN flooding.
Collection Setup
Captured within a smart home testbed consisting of various IoT devices interacting over a local network.
Recommended Research Tasks
Real-time attack classification, lightweight IDS development, and feature importance analysis for IoT networks.
Access & License
Hosted at the UCI Machine Learning Repository. Access Dataset
View Data Structure
To explore column names, data types, and sample rows, visit the official dataset page on Kaggle.
Preview on KaggleCite This Dataset
S., B., & Nagapadma, R. (2023). RT-IoT2022. [Dataset]. {UCI Machine Learning Repository. https://doi.org/10.24432/C5P338
Source metadata: {UCI Machine Learning Repository (2023) · DOI: 10.24432/C5P338
Indexed by IoTDataset.com on Feb 05, 2026
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