pirocheto/phishing-url

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
• —License: CC-BY-4.0
• —Paper: 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:

from datasets import load_dataset

dataset = load_dataset("pirocheto/phishing-url")

• —With pandas and huggingface_hub:

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:

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.