王灵矫, 吕琮霞, 郭华. SDN环境下基于支持向量机的DDoS攻击检测研究[J]. 云南大学学报(自然科学版), 2021, 43(1): 52-59. doi: 10.7540/j.ynu.20200137
引用本文: 王灵矫, 吕琮霞, 郭华. SDN环境下基于支持向量机的DDoS攻击检测研究[J]. 云南大学学报(自然科学版), 2021, 43(1): 52-59. doi: 10.7540/j.ynu.20200137
WANG Ling-jiao, LYU Cong-xia, GUO Hua. Research on DDoS attack detection based on Support Vector Machine in SDN environment[J]. Journal of Yunnan University: Natural Sciences Edition, 2021, 43(1): 52-59. DOI: 10.7540/j.ynu.20200137
Citation: WANG Ling-jiao, LYU Cong-xia, GUO Hua. Research on DDoS attack detection based on Support Vector Machine in SDN environment[J]. Journal of Yunnan University: Natural Sciences Edition, 2021, 43(1): 52-59. DOI: 10.7540/j.ynu.20200137

SDN环境下基于支持向量机的DDoS攻击检测研究

Research on DDoS attack detection based on Support Vector Machine in SDN environment

  • 摘要: 软件定义网络(Software-Defined Networks,SDN)提出了全新的架构思想,但控制器易受分布式拒绝服务(Distributed Denial of Service,DDoS)的攻击导致资源耗尽. 针对上述问题,提出了一种SDN环境下基于支持向量机(Support Vector Machine,SVM)的DDoS攻击检测算法—RF-SVM(Random Forest-SVM). 首先,根据DDoS攻击和分类特点结合数据包头信息选择关联的六维特征;然后,利用随机森林计算特征权重并筛选特征,得到一个最优特征子集;最后,采用SVM算法检测DDoS攻击,以达到较好的分类性能. 在相同场景的实验结果表明:RF-SVM算法比SVM算法和RF算法具有更高的检测率、查全率和F1值.

     

    Abstract: Software-Defined Networks (SDN) proposes a new architectural idea, but the controller is vulnerable to Distributed Denial of Service (DDoS) attacks and causes resource exhaustion. To solve the above problems, a DDoS attack detection algorithm based on Support Vector Machine (SVM) in SDN environment—RF-SVM is proposed. First, it selects the associated six-dimensional features based on the characteristics of classification and DDoS attacks combined with data packet header information. Then, it uses random forest to calculate feature weights and filter features to obtain an optimal feature subset. Finally, it uses SVM algorithm to detect DDoS attacks to achieve better classification performance. The experimental results in the same scene show that the RF-SVM algorithm has higher detection rate, recall rate and F1 value than SVM algorithm and RF algorithm.

     

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