基于机器学习的网页恶意代码检测方法

Malicious Web Pages Detection Based on Machine Learning

网络中大量的恶意网页已经成为网络用户的主要安全威胁。本文提出了一种基于机器学习分类器的网页恶意JavaScript代码分析方法。通过对训练样本训练学习,建立分类模型,最后对测试样本检测。实验表明,本方法能够有效的检测出大部分恶意网页JavaScript代码,检测准确率达到88.5%

A large number of malicious website in the network has become a major security threat of network users. This paper puts forward a kind of malicious JavaScript code analysis method based on machine learning classifier. Through the study of the training sample training, establish the classification model, finally, the detectin is tested on soonples. The experimental results show that this method can more effectively detect the most malicious JavaScript code, accuracy up to 88.5 %.