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DoS Attack Detection Based on Deep Factorization Machine in SDN

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成果类型:
期刊论文
作者:
Wang J.;Lei X.;Jiang Q.;Alfarraj O.;Tolba A.;...
通讯作者:
Kim, G.-J.
作者机构:
[Jiang Q.; Wang J.; Lei X.] School of Computer & Communication Engineering, Changsha University of Science & Technology, Changsha, 410114, China
[Tolba A.; Alfarraj O.] Computer Science Department, Community College, King Saud University, Riyadh, 11437, Saudi Arabia
[Kim G.-J.] Department of Computer Engineering, Chonnam National University, Gwangju, 61186, South Korea
通讯机构:
[Kim, G.-J.] D
Department of Computer Engineering, South Korea
语种:
英文
关键词:
deep factorization machine;denial-of-service attacks;GRMMP;Software-defined network
期刊:
Computer Systems Science and Engineering
ISSN:
0267-6192
年:
2023
卷:
45
期:
2
页码:
1727-1742
基金类别:
Funding Statement: This work was funded by the Researchers Supporting Project No. (RSP-2021/102) King Saud University, Riyadh, Saudi Arabia; This work was supported by the Research Project on Teaching Reform of General Colleges and Universities in Hunan Province (Grant No. HNJG-2020-0261), China.
机构署名:
本校为第一机构
院系归属:
计算机与通信工程学院
摘要:
Software-Defined Network (SDN) decouples the control plane of network devices from the data plane. While alleviating the problems presented in traditional network architectures, it also brings potential security risks, particularly network Denial-of-Service (DoS) attacks. While many research efforts have been devoted to identifying new features for DoS attack detection, detection methods are less accurate in detecting DoS attacks against client hosts due to the high stealth of such attacks. To solve this problem, a new method of DoS attack dete...

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