Context

This dataset has been prepared to carryout classification of webpages as malicious or benign.

Content

The dataset contains extracted attributes from websites that can be used for Classification of webpages as malicious or benign. The dataset also includes raw page content including JavaScript code that can be used as unstructured data in Deep Learning or for extracting further attributes. The data has been collected by crawling the Internet using MalCrawler [1]. The labels have been verified using the Google Safe Browsing API [2]. Attributes have been selected based on their relevance [3].

References

[1] Singh, A. K., and Navneet Goyal. "MalCrawler: A crawler for seeking and crawling malicious websites." In International Conference on Distributed Computing and Internet Technology, pp. 210-223. Springer, Cham, 2017. [2] https://developers.google.com/safe-browsing [3] Singh, A. K., and Navneet Goyal. "A Comparison of Machine Learning Attributes for Detecting Malicious Websites." In 2019 11th International Conference on Communication Systems & Networks (COMSNETS), pp. 352-358. IEEE, 2019.

Inspiration

The dataset seeks to address classification of webpages using machine learning techniques.