DDoS attack detection and defense based on hybrid deep learning model in SDN
Software defined network (SDN) is a new kind of network technology,and the security problems are the hot topics in SDN field,such as SDN control channel security,forged service deployment and external distributed denial of service (DDoS) attacks.Aiming at DDoS attack problem of security in SDN,a DDo...
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| Format: | Article |
| Language: | zho |
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Editorial Department of Journal on Communications
2018-07-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2018128/ |
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| _version_ | 1841539465116385280 |
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| author | Chuanhuang LI Yan WU Zhengzhe QIAN Zhengjun SUN Weiming WANG |
| author_facet | Chuanhuang LI Yan WU Zhengzhe QIAN Zhengjun SUN Weiming WANG |
| author_sort | Chuanhuang LI |
| collection | DOAJ |
| description | Software defined network (SDN) is a new kind of network technology,and the security problems are the hot topics in SDN field,such as SDN control channel security,forged service deployment and external distributed denial of service (DDoS) attacks.Aiming at DDoS attack problem of security in SDN,a DDoS attack detection method called DCNN-DSAE based on deep learning hybrid model in SDN was proposed.In this method,when a deep learning model was constructed,the input feature included 21 different types of fields extracted from the data plane and 5 extra self-designed features of distinguishing flow types.The experimental results show that the method has high accuracy,it’s better than the traditional support vector machine (SVM) and deep neural network (DNN) and other machine learning methods.At the same time,the proposed method can also shorten the processing time of classification detection.The detection model is deployed in SDN controller,and the new security policy is sent to the OpenFlow switch to achieve the defense against specific DDoS attack. |
| format | Article |
| id | doaj-art-e69a65ee581a41e48c1859d21de7456c |
| institution | Kabale University |
| issn | 1000-436X |
| language | zho |
| publishDate | 2018-07-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-e69a65ee581a41e48c1859d21de7456c2025-01-14T07:15:11ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2018-07-013917618759719679DDoS attack detection and defense based on hybrid deep learning model in SDNChuanhuang LIYan WUZhengzhe QIANZhengjun SUNWeiming WANGSoftware defined network (SDN) is a new kind of network technology,and the security problems are the hot topics in SDN field,such as SDN control channel security,forged service deployment and external distributed denial of service (DDoS) attacks.Aiming at DDoS attack problem of security in SDN,a DDoS attack detection method called DCNN-DSAE based on deep learning hybrid model in SDN was proposed.In this method,when a deep learning model was constructed,the input feature included 21 different types of fields extracted from the data plane and 5 extra self-designed features of distinguishing flow types.The experimental results show that the method has high accuracy,it’s better than the traditional support vector machine (SVM) and deep neural network (DNN) and other machine learning methods.At the same time,the proposed method can also shorten the processing time of classification detection.The detection model is deployed in SDN controller,and the new security policy is sent to the OpenFlow switch to achieve the defense against specific DDoS attack.http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2018128/distributed denial of servicesoftware defined networkattack detectiondeep learning |
| spellingShingle | Chuanhuang LI Yan WU Zhengzhe QIAN Zhengjun SUN Weiming WANG DDoS attack detection and defense based on hybrid deep learning model in SDN Tongxin xuebao distributed denial of service software defined network attack detection deep learning |
| title | DDoS attack detection and defense based on hybrid deep learning model in SDN |
| title_full | DDoS attack detection and defense based on hybrid deep learning model in SDN |
| title_fullStr | DDoS attack detection and defense based on hybrid deep learning model in SDN |
| title_full_unstemmed | DDoS attack detection and defense based on hybrid deep learning model in SDN |
| title_short | DDoS attack detection and defense based on hybrid deep learning model in SDN |
| title_sort | ddos attack detection and defense based on hybrid deep learning model in sdn |
| topic | distributed denial of service software defined network attack detection deep learning |
| url | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2018128/ |
| work_keys_str_mv | AT chuanhuangli ddosattackdetectionanddefensebasedonhybriddeeplearningmodelinsdn AT yanwu ddosattackdetectionanddefensebasedonhybriddeeplearningmodelinsdn AT zhengzheqian ddosattackdetectionanddefensebasedonhybriddeeplearningmodelinsdn AT zhengjunsun ddosattackdetectionanddefensebasedonhybriddeeplearningmodelinsdn AT weimingwang ddosattackdetectionanddefensebasedonhybriddeeplearningmodelinsdn |