Duplicate from pirocheto/phishing-url

Co-authored-by: pirocheto <pirocheto@users.noreply.huggingface.co>

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2010.12847.pdf

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README.md

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+---
+license: cc-by-4.0
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: data/train.parquet
+  - split: test
+    path: data/test.parquet
+task_categories:
+- text-classification
+- tabular-classification
+- token-classification
+- text2text-generation
+size_categories:
+- n<1K
+annotations_creators:
+- found
+tags:
+- phishing
+- url
+- security
+language:
+- en
+pretty_name: TabNetone
+---
+
+
+
+# Dataset Description
+
+The provided dataset includes **11430** URLs with **87** extracted features.  
+The dataset are designed to be used as a benchmark for machine learning based **phishing detection** systems.  
+The datatset is balanced, it containes exactly 50% phishing and 50% legitimate URLs.  
+
+Features are from three different classes:
+- **56** extracted from the structure and syntax of URLs
+- **24** extracted from the content of their correspondent pages
+- **7** are extracetd by querying external services.
+
+
+The dataset was partitioned randomly into training and testing sets, with a ratio of **two-thirds for training** and **one-third for testing**.
+
+## Details
+
+- **Funded by:** Abdelhakim Hannousse, Salima Yahiouche
+- **Shared by:** [pirocheto](https://github.com/pirocheto)
+- **License:** [CC-BY-4.0](https://creativecommons.org/licenses/by/4.0/)
+- **Paper:** [https://arxiv.org/abs/2010.12847](https://arxiv.org/abs/2010.12847)
+
+## Source Data
+
+The diagram below illustrates the procedure for creating the corpus.  
+For details, please refer to the paper.
+
+<div align="center">
+  <img src="images/source_data.png" alt="Diagram source data">
+</div>
+
+<p align="center">
+  <em>Source: Extract form the <a href="https://arxiv.org/abs/2010.12847">paper</a></em>
+</p>
+
+## Load Dataset
+
+- With **datasets**:
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("pirocheto/phishing-url")
+```
+
+- With **pandas** and **huggingface_hub**:
+```python
+import pandas as pd
+from huggingface_hub import hf_hub_download
+
+REPO_ID = "pirocheto/phishing-url"
+FILENAME = "data/train.parquet"
+
+df = pd.read_parquet(
+    hf_hub_download(repo_id=REPO_ID, filename=FILENAME, repo_type="dataset")
+)
+```
+
+- With **pandas** only:
+```python
+import pandas as pd
+
+url = "https://huggingface.co/datasets/pirocheto/phishing-url/resolve/main/data/train.parquet"
+df = pd.read_parquet(url)
+```
+
+## Citation
+
+To give credit to the creators of this dataset, please use the following citation in your work:
+
+- BibTeX format
+
+```
+@article{Hannousse_2021,
+   title={Towards benchmark datasets for machine learning based website phishing detection: An experimental study},
+   volume={104},
+   ISSN={0952-1976},
+   url={http://dx.doi.org/10.1016/j.engappai.2021.104347},
+   DOI={10.1016/j.engappai.2021.104347},
+   journal={Engineering Applications of Artificial Intelligence},
+   publisher={Elsevier BV},
+   author={Hannousse, Abdelhakim and Yahiouche, Salima},
+   year={2021},
+   month=sep, pages={104347} }
+```
+
+- APA format
+
+```
+Hannousse, A., & Yahiouche, S. (2021).
+Towards benchmark datasets for machine learning based website phishing detection: An experimental study.
+Engineering Applications of Artificial Intelligence, 104, 104347.
+```

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