Web page phishing detection

The provided dataset includes 11430 URLs with 87 extracted features. The dataset are designed to be used as a a benchmark for machine learning based phishing detection systems. Features are from three different classes: 56 extracted from the structure and syntax of URLs, 24 extracted from the content of their correspondent pages and 7 are extracetd by querying external services. The datatset is balanced, it containes exactly 50% phishing and 50% legitimate URLs. Associated to the dataset, we provide Python scripts used for the extraction of the features for potential replication or extension. Datasets are constructed on May 2020. dataset_A: contains a list a URLs together with their DOM tree objects that can be used for replication and experimenting new URL and content-based features overtaking short-time living of phishing web pages. dataset_B: containes the extracted feature values that can be used directly as inupt to classifiers for examination. Note that the data in this dataset are indexed with URLs so that one need to remove the index before experimentation.

本数据集包含11430个统一资源定位符（Uniform Resource Locator，URL），共提取得到87项特征，旨在作为基于机器学习的钓鱼检测系统的基准测试数据集。特征分为三大类别：56项源自URL的结构与语法，24项源自对应网页的内容，剩余7项通过查询外部服务提取得到。本数据集类别均衡，钓鱼URL与合法URL各占50%。为便于研究复现或扩展，本数据集附带了用于特征提取的Python脚本。数据集构建于2020年5月。dataset_A：包含一组URL及其文档对象模型（Document Object Model，DOM）树对象，可用于复现研究以及针对钓鱼网页短时存活的特性开展新型URL及基于内容的特征实验。dataset_B：包含已提取的特征值，可直接作为分类器的输入用于检测实验。请注意，本数据集的数据以URL作为索引，因此在开展实验前需要移除索引项。