计算机应用研究2018，Vol.35Issue(3)：911-915,5.DOI:10.3969/j.issn.1001-3695.2018.03.057
SDN环境下基于BP神经网络的DDoS攻击检测方法
DDoS attack detection based on BPNN in software defined networks
摘要
Abstract
Software definition network is a new network architecture that achieves a centralized network control.Although centralized control is the main advantage of SDN,but if subject to DDoS attacks,the information will be not reachable,it also likely to cause a single point of failure.In order to mitigate this threat,this paper proposed a DDoS attack detection method based on SDN centralized control.This algorithm obtained the flow table items of OpenFlow switch,analyzed the characteristics of DDoS attacks in SDN environment,and extracted six characteristics related to attacks.By analyzing the changes of the six eigenvalues,it used BP neural network algorithm to classify the training samples to achieve the DDoS attack detection.The experimental results show that the method can improve the recognition rate and reduce the detection time.The effectiveness of the method is verified by the deployment in a software-defined network environment.关键词
软件定义网络/分布式拒绝服务攻击/反向传播神经网络/特征值/攻击检测Key words
software definition network/DDoS attack/BP neural network/eigenvalues/attack detection分类
信息技术与安全科学引用本文复制引用
王晓瑞,庄雷,胡颖,王国卿,马丁,景晨凯..SDN环境下基于BP神经网络的DDoS攻击检测方法[J].计算机应用研究,2018,35(3):911-915,5.基金项目
国家“973”计划资助项目(2012CB315901) （2012CB315901）
国家自然科学基金资助项目(61379079) （61379079）
河南省科技攻关项目(122102210042) （122102210042）
