Abstract:

With the popularity of the network, the number of web pages is in rapid growth, and the proportion of the malicious web page growth rate also shows an upward trend. The detection of malicious web pages has been the focus and difficulty of network security research. The traditional malicious webpage detection model is more and more difficult to deal with the new situation. The application of machine learning algorithm in the field of malicious webpage is a way to break the limitation of traditional malicious webpage. In this paper, a malicious web page detection model based on machine learning has been developed. The model classifies the web pages by collecting the characteristic information like URL、HOST information and the content of various web pages using machine learning algorithm, and it has achieved more excellent classification effect comparing to the prior work.

Key words: malicious Web page, phishing webpage, machine learning, front end security