A Survey of Public IoT Datasets for Network Security Research

Abstract

Publicly available datasets are an indispensable tool for researchers, as they allow testing new algorithms on a wide range of different scenarios and making scientific experiments verifiable and reproducible. Research in IoT security is no exception. In particular, the design of traffic classification and intrusion detection solutions for network security relies on network traces obtained from real networks or realistic testbeds. In this paper, we provide a detailed survey on the existing datasets containing IoT network traffic. We classify them according to several features that help researchers quickly find the datasets that fit their specific needs. In total, we survey 74 datasets that we found by analyzing more than 100 scientific articles. We also discuss the weaknesses of existing datasets, identify challenges, and point to future directions for creating new IoT datasets.