Domain name generation algorithm based on improved Markov chain
First, a combination of multiple strategies were used to conduct preliminary screening of subdomain names, including dictionary enumeration, search engine mining, and website information crawling. Then, the improved Markov model algorithm was used to analyze the filtered data, and new subdomain name...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Editorial Department of Journal on Communications
2024-11-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2024253/ |
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| _version_ | 1841537091424485376 |
|---|---|
| author | QIAN Zhiye LI Xue LI Suogang |
| author_facet | QIAN Zhiye LI Xue LI Suogang |
| author_sort | QIAN Zhiye |
| collection | DOAJ |
| description | First, a combination of multiple strategies were used to conduct preliminary screening of subdomain names, including dictionary enumeration, search engine mining, and website information crawling. Then, the improved Markov model algorithm was used to analyze the filtered data, and new subdomain names were generated and added to the result set. Thereafter, the data was checked and verified for authenticity. If the data did not meet the criteria, the analysis process was repeated. Finally, a rigorously validated data set was formed. The proposed algorithm significantly improves the efficiency and coverage of subdomain discovery, effectively making up for the shortcomings of traditional methods. |
| format | Article |
| id | doaj-art-1ee6ed77e759415bbf148c7249d39913 |
| institution | Kabale University |
| issn | 1000-436X |
| language | zho |
| publishDate | 2024-11-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-1ee6ed77e759415bbf148c7249d399132025-01-14T08:46:29ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2024-11-0145525879661217Domain name generation algorithm based on improved Markov chainQIAN ZhiyeLI XueLI SuogangFirst, a combination of multiple strategies were used to conduct preliminary screening of subdomain names, including dictionary enumeration, search engine mining, and website information crawling. Then, the improved Markov model algorithm was used to analyze the filtered data, and new subdomain names were generated and added to the result set. Thereafter, the data was checked and verified for authenticity. If the data did not meet the criteria, the analysis process was repeated. Finally, a rigorously validated data set was formed. The proposed algorithm significantly improves the efficiency and coverage of subdomain discovery, effectively making up for the shortcomings of traditional methods.http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2024253/domain name generation algorithmsubdomain miningDNS resolutionnetwork security |
| spellingShingle | QIAN Zhiye LI Xue LI Suogang Domain name generation algorithm based on improved Markov chain Tongxin xuebao domain name generation algorithm subdomain mining DNS resolution network security |
| title | Domain name generation algorithm based on improved Markov chain |
| title_full | Domain name generation algorithm based on improved Markov chain |
| title_fullStr | Domain name generation algorithm based on improved Markov chain |
| title_full_unstemmed | Domain name generation algorithm based on improved Markov chain |
| title_short | Domain name generation algorithm based on improved Markov chain |
| title_sort | domain name generation algorithm based on improved markov chain |
| topic | domain name generation algorithm subdomain mining DNS resolution network security |
| url | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2024253/ |
| work_keys_str_mv | AT qianzhiye domainnamegenerationalgorithmbasedonimprovedmarkovchain AT lixue domainnamegenerationalgorithmbasedonimprovedmarkovchain AT lisuogang domainnamegenerationalgorithmbasedonimprovedmarkovchain |