基于OPRFM的HTTP-DDoS攻击检测方法

Detection Method of HTTP-DDoS Attack Based on OPRFM

DDoS攻击是网络安全领域面临的一个重大问题。本文旨在提高DDoS攻击检测分类的能力,提出新的改进的随机森林算法,并在此基础上提出一种检测DDoS攻击的改进随机森林分类模型。利用公开的CICIDS2017数据集进行验证,实验表明,与随机森林、决策树、支持向量机算法相比,提出的算法在精确率、召回率和F1值方面显示出显著的改善。

DDoS attack is a major problem in the field of network security. This paper aims to improve the ability of detection and classification of DDoS attacks, proposes a new improved random forest algorithm, and on this basis, proposes an improved random forest classification model to detect DDoS attacks. The experiments show that compared with the random forest algorithm, decision tree algorithm and support vector machine algorithm, the proposed algorithm shows significant improvement in accuracy, recall rate and F1 value.