Phishing Websites Datast

One of the challenges faced by our research was the unavailability of reliable training datasets. In fact, this challenge faces any researcher in the field. However, although plenty of articles about predicting phishing websites using data mining techniques have been disseminated these days, no reliable training dataset has been published publically, maybe because there is no agreement in literature on the definitive features that characterize phishing websites, hence it is difficult to shape a dataset that covers all possible features.
In this dataset, we shed light on the important features that have proved to be sound and effective in predicting phishing websites. In addition, we proposed some new features, experimentally assign new rules to some well-known features and update some other features.

本研究团队所面临的挑战之一，即为缺乏可靠的训练数据集。实际上，这一挑战在相关研究领域普遍存在。尽管近年来有关利用数据挖掘技术预测钓鱼网站的大量文章已广泛传播，然而，尚无可靠的训练数据集公开发表，或许是由于文献中对于界定钓鱼网站的特征尚未达成共识，因此构建一个涵盖所有可能特征的数据库变得尤为困难。在本数据集中，我们揭示了在预测钓鱼网站方面已证实为稳健有效的关键特征。此外，我们还提出了一些新的特征，对某些知名特征进行了实验性的规则分配，并对其他特征进行了更新。