Efficient Joint Detection and Defense Mechanism for DDoS Attack in SDN

被引：1
|
作者：
Zeng R.-F. [1 ]
Gao Y. [2 ]
Wang X.-W. [2 ]
Zhang B. [2 ]
机构：
[1] School of Software, Northeastern University, Shenyang
[2] School of Computer Science & Engineering, Northeastern University, Shenyang
来源：
Dongbei Daxue Xuebao/Journal of Northeastern University | 2020年 / 41卷 / 09期
关键词：
Distributed denial of service attack; Improved self-organizing mapping algorithm; Multidimensional conditional entropy algorithm; Priority; Software-defined networking;
D O I：
10.12068/j.issn.1005-3026.2020.09.001
中图分类号：
学科分类号：
摘要：
In order to defend against the DDoS attacks for SDN(software-defined networking) controller, this paper proposed an efficient joint detection and defense mechanism. The joint detection part adopted the combination of improved self-organizing mapping algorithm and multidimensional conditional entropy algorithm. By combining the two methods, the purpose of joint detection was achieved. The joint defense part includes a conventional defense module and a fast defense module, which adopts different defense strategies for different detection results by adjusting the priority. Extensive experimental results showed that the joint detection mechanism can achieve a detection rate of 95.2%, and the response time of the joint defense mechanism to the controller can be reduced by 0.11 s on average, compared with the single defense mechanism. © 2020, Editorial Department of Journal of Northeastern University. All right reserved.
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页码：1217 / 1222
页数：5
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