malicious and benign websites

One important topic to work is to create a good set of malicious web characteristics, because it is difficult to find one updated and with a research work to support it . This dataset is a another research production of my bachelor students, this is a result of a project that consisted to evaluate classification models to predict malicious and benign websites through their application layer and network characteristics. The data were obtained by a process that included different sources of benign and malicious URL, all of them were verified and used in a low interactive client honeypot in order to get their network traffic, furthermore, we used some tools to get other more information, such as the server country with Whois. This is the first version, but, we have some results of the application of machine learning classifiers in a bachelor thesis and in an article, so, all the data process making and the data description are in above works. But, maybe in the next days I will provide a resume of these in this page. If your papers or other works use our dataset, please cite our paper as follows. Urcuqui, C., Navarro, A., Osorio, J., & Garcıa, M. (2017). Machine Learning Classifiers to Detect Malicious Websites. CEUR Workshop Proceedings. Vol 1950, 14-17. If you need an article of the websites cybersecurity state of the art, you can find it in english and spanish: Urcuqui, C., Peña, M. G., Quintero, J. L. O., & Cadavid, A. N. (2017). Antidefacement. Sistemas & Telemática, 14(39), 9-27. If you have any question or feedback, please do not dude to write at the next email:[e-mail]

一项至关重要的研究课题在于构建一套完善的恶意网页特征集合，鉴于其难以寻觅更新且附有研究支撑的实例。本数据集系我的本科学生所进行的一项研究项目的成果，旨在通过应用层和网络特征对恶意与良性网站进行分类预测。数据采集过程涵盖多种良性及恶意URL来源，所有数据均经过验证并应用于低交互式客户端蜜罐中，以获取其网络流量。此外，我们还利用一些工具获取了更多元的信息，例如通过Whois查询服务器所在国家。目前，此为数据集的初始版本。然而，我们已在本科论文及一篇文章中应用了机器学习分类器并取得了一些成果，因此，所有数据处理及数据描述均可在上述作品中查阅。未来几日内，我或许会在此页面上提供一份简报。若您的研究或作品使用了我们的数据集，请按照以下格式引用我们的论文：Urcuqui, C., Navarro, A., Osorio, J., & Garcıa, M. (2017). Machine Learning Classifiers to Detect Malicious Websites. CEUR Workshop Proceedings. Vol 1950, 14-17。如需了解关于网站网络安全现状的综述文章，您可以在英文和西班牙语版本中找到：Urcuqui, C., Peña, M. G., Quintero, J. L. O., & Cadavid, A. N. (2017). Antidefacement. Sistemas & Telemática, 14(39), 9-27。如有任何疑问或反馈，请勿犹豫，通过以下邮箱与我们联系：[e-mail]。