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--- |
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license: cc-by-4.0 |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: "data/train.parquet" |
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- split: test |
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path: "data/test.parquet" |
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task_categories: |
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- text-classification |
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- tabular-classification |
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size_categories: |
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- n<1K |
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annotations_creators: |
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- found |
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tags: |
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- phishing |
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- url |
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- security |
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--- |
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# Dataset Description |
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The provided dataset includes **11430** URLs with **87** extracted features. |
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The dataset are designed to be used as a benchmark for machine learning based **phishing detection** systems. |
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The datatset is balanced, it containes exactly 50% phishing and 50% legitimate URLs. |
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Features are from three different classes: |
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- **56** extracted from the structure and syntax of URLs |
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- **24** extracted from the content of their correspondent pages |
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- **7** are extracetd by querying external services. |
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The dataset was partitioned randomly into training and testing sets, with a ratio of **two-thirds for training** and **one-third** for testing. |
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## Details |
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- **Funded by:** Abdelhakim Hannousse, Salima Yahiouche |
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- **Shared by:** [pirocheto](https://github.com/pirocheto) |
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- **License:** [CC-BY-4.0](https://creativecommons.org/licenses/by/4.0/) |
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- **Paper:** [https://arxiv.org/abs/2010.12847](https://arxiv.org/abs/2010.12847) |
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## Source Data |
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The diagram below illustrates the procedure for creating the corpus. |
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For details, please refer to the paper. |
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<div align="center"> |
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<img src="images/source_data.png" alt="Diagram source data"> |
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</div> |
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<p align="center"> |
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<em>Source: Extract form the <a href="https://arxiv.org/abs/2010.12847">paper</a></em> |
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</p> |
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## Load Dataset |
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- With **datasets**: |
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```python |
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from datasets import load_dataset |
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dataset = load_dataset("pirocheto/phishing-url") |
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``` |
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- With **pandas** and **huggingface_hub**: |
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```python |
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import pandas as pd |
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from huggingface_hub import hf_hub_download |
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REPO_ID = "pirocheto/phishing-url" |
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FILENAME = "data/train.parquet" |
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df = pd.read_parquet( |
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hf_hub_download(repo_id=REPO_ID, filename=FILENAME, repo_type="dataset") |
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) |
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``` |
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- With **pandas** only: |
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```python |
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import pandas as pd |
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url = "https://huggingface.co/datasets/pirocheto/phishing-url/resolve/main/data/train.parquet" |
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df = pd.read_parquet(url) |
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``` |
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## Citation |
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To give credit to the creators of this dataset, please use the following citation in your work: |
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- BibTeX format |
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``` |
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@article{Hannousse_2021, |
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title={Towards benchmark datasets for machine learning based website phishing detection: An experimental study}, |
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volume={104}, |
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ISSN={0952-1976}, |
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url={http://dx.doi.org/10.1016/j.engappai.2021.104347}, |
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DOI={10.1016/j.engappai.2021.104347}, |
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journal={Engineering Applications of Artificial Intelligence}, |
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publisher={Elsevier BV}, |
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author={Hannousse, Abdelhakim and Yahiouche, Salima}, |
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year={2021}, |
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month=sep, pages={104347} } |
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``` |
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- APA format |
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``` |
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Hannousse, A., & Yahiouche, S. (2021). |
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Towards benchmark datasets for machine learning based website phishing detection: An experimental study. |
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Engineering Applications of Artificial Intelligence, 104, 104347. |
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``` |
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