bencorn/CIC-IoT-2023
收藏Hugging Face2026-03-15 更新2026-03-29 收录
下载链接:
https://hf-mirror.com/datasets/bencorn/CIC-IoT-2023
下载链接
链接失效反馈官方服务:
资源简介:
---
license: cc
---
应用场景:
提供机构:
bencorn相关数据集
casscloud/CIC-IoT-2023
CIC-IoT-2023物联网入侵检测数据集是由加拿大网络安全研究所(CIC)提供的原始数据集的子采样和预处理版本,专为机器学习评估设计。该数据集用于物联网(IoT)环境中的网络入侵检测,支持二元分类(良性 vs 攻击)和多元分类(34个细粒度攻击类型或8个攻击类别)。数据集包含1,342,314行数据,其中良性流量199,988行,攻击流量1,142,326行,覆盖33种攻击子类型,分为7个主要
Hugging Face2026-05-10 更新00
lacg030175/CIC-IoT-2023
--- language: - en license: cc-by-4.0 size_categories: - 1M<n<10M task_categories: - tabular-classification tags: - network-intrusion-detection - cybersecurity - CIC-IoT-2023 - IoT - IDS - binary-clas
Hugging Face2026-04-02 更新30
Supplementary material - An Optimized Gradient Boosting Framework for IoT Intrusion Detection: A Comprehensive Evaluation on the CIC-IoT-2023 Dataset
This repository provides the complete supplementary material for the study “An Optimized Gradient Boosting Framework for IoT Intrusion Detection: A Comprehensive Evaluation on the CIC-IoT-2023 Dataset
Zenodo2025-10-14 更新00
siyam21/CIC-IoT-2023
CIC-IoT-2023物联网入侵检测数据集是来自加拿大网络安全研究所的一个数据集,经过子采样和预处理,用于机器学习评估。该数据集针对物联网环境的大规模攻击设计,包含流量级别的数值特征,用于二分类和多分类任务。数据集提供了两种配置:默认的random_3way配置(80%训练、10%测试、10%验证,采用分层随机分割,确保训练、测试和验证集完全分离)和random配置(80%训练、20%测试,用于
Hugging Face2026-05-18 更新00
Supplementary material - An Optimized Gradient Boosting Framework for IoT Intrusion Detection: A Comprehensive Evaluation on the CIC-IoT-2023 Dataset
This repository provides the complete supplementary material for the study “An Optimized Gradient Boosting Framework for IoT Intrusion Detection: A Comprehensive Evaluation on the CIC-IoT-2023 Dataset
Zenodo2025-10-15 更新00



