LDoS attack detection method based on simple statistical features
Traditional low-rate denial of service (LDoS) attack detection methods were complex in feature extraction, high in computational cost, single in experimental data background settings, and outdated in attack scenarios, so it was difficult to meet the demand for LDoS attack detection in a real network...
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| Format: | Article |
| Language: | zho |
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Editorial Department of Journal on Communications
2022-11-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2022216/ |
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| _version_ | 1841539963083030528 |
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| author | Xueyuan DUAN Yu FU Kun WANG Bin LI |
| author_facet | Xueyuan DUAN Yu FU Kun WANG Bin LI |
| author_sort | Xueyuan DUAN |
| collection | DOAJ |
| description | Traditional low-rate denial of service (LDoS) attack detection methods were complex in feature extraction, high in computational cost, single in experimental data background settings, and outdated in attack scenarios, so it was difficult to meet the demand for LDoS attack detection in a real network environment.By studying the principle of LDoS attack and analyzing the features of LDoS attack traffic, a detection method of LDoS attack based on simple statistical features of network traffic was proposed.By using the simple statistical features of network traffic packets, the detection data sequence was constructed, the time correlation features of input samples were extracted by deep learning technology, and the LDoS attack judgment was made according to the difference between the reconstructed sequence and the original input sequence.Experimental results show that the proposed method can effectively detect the LDoS attack traffic in traffic and has strong adaptability to heterogeneous network traffic. |
| format | Article |
| id | doaj-art-313848ddfa1a4f0dae13c9c72d74b538 |
| institution | Kabale University |
| issn | 1000-436X |
| language | zho |
| publishDate | 2022-11-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-313848ddfa1a4f0dae13c9c72d74b5382025-01-14T06:29:18ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2022-11-0143536459393565LDoS attack detection method based on simple statistical featuresXueyuan DUANYu FUKun WANGBin LITraditional low-rate denial of service (LDoS) attack detection methods were complex in feature extraction, high in computational cost, single in experimental data background settings, and outdated in attack scenarios, so it was difficult to meet the demand for LDoS attack detection in a real network environment.By studying the principle of LDoS attack and analyzing the features of LDoS attack traffic, a detection method of LDoS attack based on simple statistical features of network traffic was proposed.By using the simple statistical features of network traffic packets, the detection data sequence was constructed, the time correlation features of input samples were extracted by deep learning technology, and the LDoS attack judgment was made according to the difference between the reconstructed sequence and the original input sequence.Experimental results show that the proposed method can effectively detect the LDoS attack traffic in traffic and has strong adaptability to heterogeneous network traffic.http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2022216/statistical featuresdeep learninglow-rate denial of serviceattack detection |
| spellingShingle | Xueyuan DUAN Yu FU Kun WANG Bin LI LDoS attack detection method based on simple statistical features Tongxin xuebao statistical features deep learning low-rate denial of service attack detection |
| title | LDoS attack detection method based on simple statistical features |
| title_full | LDoS attack detection method based on simple statistical features |
| title_fullStr | LDoS attack detection method based on simple statistical features |
| title_full_unstemmed | LDoS attack detection method based on simple statistical features |
| title_short | LDoS attack detection method based on simple statistical features |
| title_sort | ldos attack detection method based on simple statistical features |
| topic | statistical features deep learning low-rate denial of service attack detection |
| url | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2022216/ |
| work_keys_str_mv | AT xueyuanduan ldosattackdetectionmethodbasedonsimplestatisticalfeatures AT yufu ldosattackdetectionmethodbasedonsimplestatisticalfeatures AT kunwang ldosattackdetectionmethodbasedonsimplestatisticalfeatures AT binli ldosattackdetectionmethodbasedonsimplestatisticalfeatures |