metadata

license: cc-by-4.0
configs:
  - config_name: default
    data_files:
      - split: data
        path: data.csv
task_categories:
  - text-classification
  - tabular-classification
size_categories:
  - n<1K
annotations_creators:
  - found
tags:
  - phishing
  - url
  - security

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.

Details

Funded by: Abdelhakim Hannousse, Salima Yahiouche
Shared by: pirocheto
License: CC-BY-4.0
Paper: https://arxiv.org/abs/2010.12847

Source Data

Source: Extract form the paper

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.