cic-ids2017
CICIDS2017
CICIDS2017 (Unofficial mirror on Hugging Face)
Dataset Summary
This repository provides a mirrored copy of the CICIDS2017 dataset files (PCAPs and accompanying archives) for easier access and reproducibility in ML/security research workflows.
Important: This is not the original distribution. Please refer to the official source for authoritative documentation, updates, and terms.
Source / Origin
Original dataset name: CICIDS2017
Original publisher: Canadian… See the full description on the dataset page: https://huggingface.co/datasets/bencorn/CICIDS2017.cic-ids-2017
CIC-IDS-2017 Dataset
This repository contains the CIC-IDS-2017 dataset with the original PCAPs and the CSVs converted to Parquet format for easier use.
Dataset Structure
Configurations
machine_learning: Contains the flow-based features used for ML training (Converted from MachineLearningCVE CSVs).
traffic_labels: Contains the labelled flows (Converted from TrafficLabelling CSVs). Timestamps have been normalized to UTC.
Raw Data
The pcap/ folder… See the full description on the dataset page: https://huggingface.co/datasets/bvsam/cic-ids-2017.CIC-IDS2017We have developed a Python package as a wrapper around Hugging Face Hub and Hugging Face Datasets library to access this dataset easily.
NIDS Datasets
The nids-datasets package provides functionality to download and utilize specially curated and extracted datasets from the original UNSW-NB15 and CIC-IDS2017 datasets. These datasets, which initially were only flow datasets, have been enhanced to include packet-level information from the raw PCAP files. The dataset contains both… See the full description on the dataset page: https://huggingface.co/datasets/rdpahalavan/CIC-IDS2017.CIC-IDS2017The CICIDS2017 dataset consists of labeled network flows, including full packet payloads in pcap format, the corresponding profiles and the labeled flows (GeneratedLabelledFlows.zip) and CSV files for machine and deep learning purpose (MachineLearningCSV.zip) are publicly available for researchers. If you are using our dataset, you should cite our related paper which outlining the details of the dataset and its underlying principles:
Iman Sharafaldin, Arash Habibi Lashkari, and Ali A.… See the full description on the dataset page: https://huggingface.co/datasets/c01dsnap/CIC-IDS2017.CICIDS2017
CICIDS2017 Network Intrusion Detection Dataset
The CICIDS2017 dataset from the Canadian Institute for Cybersecurity, provided with temporal and random splits for fair evaluation.
Configurations
temporal (default) — Day-Based Temporal Split
Note: standard is an alias for temporal — both load the same data.
Train on Monday-Thursday, test on Friday. The model must generalize to unseen attack types (DDoS, Botnet, PortScan).
from datasets import load_dataset
ds =… See the full description on the dataset page: https://huggingface.co/datasets/lacg030175/CICIDS2017.cic-ids-2017
CIC-IDS-2017 Dataset
This repository contains the CIC-IDS-2017 dataset with the original PCAPs and the CSVs converted to Parquet format for easier use.
Dataset Structure
Configurations
machine_learning: Contains the flow-based features used for ML training (Converted from MachineLearningCVE CSVs).
traffic_labels: Contains the labelled flows (Converted from TrafficLabelling CSVs). Timestamps have been normalized to UTC.
Raw Data
The pcap/ folder… See the full description on the dataset page: https://huggingface.co/datasets/Ariasyah/cic-ids-2017.