基于DGA域名检测方法的选优方案研究

Research on the Optimal Scheme Based on DGA Domain Name Detection Method

该文介绍了DGA域名的研究背景和价值,DGA域名的特点、分类和基本定义。然后介绍了人工智能中几种流行的智能算法,例如XGBoost、朴素贝叶斯、多层感知器和循环神经网络。接着介绍了几种特征提取的方法,包括N-Gram模型、统计域名特征模型和字符序列模型。最后对特征提取和相关算法进行实验,并对结果进行对比分析,获取较优的特征提取和算法组合。

This paper introduces the research background and value of DGA domain name,the characteristics,classification and basic definition of DGA domain name.Then it introduces several popular intelligent algorithms in artificial intelligence,such as xgboost,naive Bayes,multilayer perceptron and cyclic neural network.Then several feature extraction methods are introduced,including N-gram model,statistical domain name feature model and character sequence model.Finally,the experiments of feature extraction and related algorithms are carried out,and the results are compared and analyzed to obtain better feature extraction and algorithm combination.