derived CICIoT 2023 datasets

Published: 5 December 2025| Version 1 | DOI: 10.17632/x36s52ybfw.1
Contributors:
Hiba El Balbali, Anas Abou El Kalam

Description

These datasets is derived from the publicly available CIC IoT 2023 described in: DOI: https://doi.org/10.3390/s23135941. The original data are available at: https://www.unb.ca/cic/datasets/iotdataset-2023.html These derived datasets are intended to support research on intrusion detection using machine learning and deep learning models. The two datasets included are: Binary Classification Dataset (binary_data) This version groups all attack types into a single “Attack” class and retains the normal traffic as a separate “Benign” class. It is designed to evaluate binary intrusion detection models. Eight-Class Classification Dataset (8class_data) This version preserves a more detailed categorization of attacks by organizing them into eight meaningful classes. This allows researchers to study multi-class intrusion detection performance in more complex environments.ttps://www.unb.ca/cic/datasets/iotdataset-2023.html

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Categories

Intrusion Detection, Internet of Things

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