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---
pretty_name: "CIC-IDS-2017"
language:
- en
tags:
- cybersecurity
- network
- pcap
- flow
task_categories:
- tabular-classification
configs:
- config_name: machine_learning
data_files: "machine_learning/*.parquet"
- config_name: traffic_labels
data_files: "traffic_labels/*.parquet"
---
# CIC-IDS-2017 Dataset
This repository contains the [CIC-IDS-2017 dataset](https://www.unb.ca/cic/datasets/ids-2017.html) with the original PCAPs and the CSVs converted to Parquet format for easier use.
## Dataset Structure
### Configurations
1. **`machine_learning`**: Contains the flow-based features used for ML training (Converted from `MachineLearningCVE` CSVs).
2. **`traffic_labels`**: Contains the labelled flows (Converted from `TrafficLabelling` CSVs). Timestamps have been normalized to UTC.
### Raw Data
The `pcap/` folder contains the original PCAP files. These are not part of the Hugging Face Dataset Viewer but can be downloaded via Git LFS.
## License
_(Copied from original dataset License section)_
The **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. Ghorbani, “Toward Generating a New Intrusion Detection Dataset and Intrusion Traffic Characterization”, 4th International Conference on Information Systems Security and Privacy (ICISSP), Portugal, January 2018.
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