Study of high-speed malicious Web page detection system based on two-step classifier
In view of the increasing number of new Web pages and the increasing pressure of traditional detection methods,the naive Bayesian algorithm and the support vector machine algorithm were used to design and implement a malicious Web detection system with both efficiency and function,TSMWD ,two-step ma...
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| Format: | Article |
| Language: | English |
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POSTS&TELECOM PRESS Co., LTD
2017-08-01
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| Series: | 网络与信息安全学报 |
| Subjects: | |
| Online Access: | http://www.infocomm-journal.com/cjnis/CN/10.11959/j.issn.2096-109x.2017.00186 |
| _version_ | 1811255731707445248 |
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| author | Zheng-qi WANG,Xiao-bing FENG,Chi ZHANG |
| author_facet | Zheng-qi WANG,Xiao-bing FENG,Chi ZHANG |
| author_sort | Zheng-qi WANG,Xiao-bing FENG,Chi ZHANG |
| collection | DOAJ |
| description | In view of the increasing number of new Web pages and the increasing pressure of traditional detection methods,the naive Bayesian algorithm and the support vector machine algorithm were used to design and implement a malicious Web detection system with both efficiency and function,TSMWD ,two-step malicious Web page detection.The first step of detection system was mainly used to filter a large number of normal Web pages,which was characterized by high efficiency,speed,update iteration easy,real rate priority.After the former filter,due to the limited number of samples,the main pursuit of the second step was the detection rate.The experimental results show that the proposed scheme can improve the detection speed of the system under the condition that the overall detection accuracy is basically the same,and can accept more detection requests in certain time. |
| first_indexed | 2024-04-12T17:28:13Z |
| format | Article |
| id | doaj.art-7c74b333e4f540b2970731be0cae9115 |
| institution | Directory Open Access Journal |
| issn | 2096-109X |
| language | English |
| last_indexed | 2024-04-12T17:28:13Z |
| publishDate | 2017-08-01 |
| publisher | POSTS&TELECOM PRESS Co., LTD |
| record_format | Article |
| series | 网络与信息安全学报 |
| spelling | doaj.art-7c74b333e4f540b2970731be0cae91152022-12-22T03:23:12ZengPOSTS&TELECOM PRESS Co., LTD网络与信息安全学报2096-109X2017-08-0138446010.11959/j.issn.2096-109x.2017.00186Study of high-speed malicious Web page detection system based on two-step classifierZheng-qi WANG,Xiao-bing FENG,Chi ZHANG0University of Science and Technology of China,Hefei 230026,China ; Key Laboratory of Electromagnetic Space Information,Chinese Academy of Sciences,Hefei 230026,ChinaIn view of the increasing number of new Web pages and the increasing pressure of traditional detection methods,the naive Bayesian algorithm and the support vector machine algorithm were used to design and implement a malicious Web detection system with both efficiency and function,TSMWD ,two-step malicious Web page detection.The first step of detection system was mainly used to filter a large number of normal Web pages,which was characterized by high efficiency,speed,update iteration easy,real rate priority.After the former filter,due to the limited number of samples,the main pursuit of the second step was the detection rate.The experimental results show that the proposed scheme can improve the detection speed of the system under the condition that the overall detection accuracy is basically the same,and can accept more detection requests in certain time.http://www.infocomm-journal.com/cjnis/CN/10.11959/j.issn.2096-109x.2017.00186malicious web page detectionnetwork securitymachine learningfeature extraction |
| spellingShingle | Zheng-qi WANG,Xiao-bing FENG,Chi ZHANG Study of high-speed malicious Web page detection system based on two-step classifier 网络与信息安全学报 malicious web page detection network security machine learning feature extraction |
| title | Study of high-speed malicious Web page detection system based on two-step classifier |
| title_full | Study of high-speed malicious Web page detection system based on two-step classifier |
| title_fullStr | Study of high-speed malicious Web page detection system based on two-step classifier |
| title_full_unstemmed | Study of high-speed malicious Web page detection system based on two-step classifier |
| title_short | Study of high-speed malicious Web page detection system based on two-step classifier |
| title_sort | study of high speed malicious web page detection system based on two step classifier |
| topic | malicious web page detection network security machine learning feature extraction |
| url | http://www.infocomm-journal.com/cjnis/CN/10.11959/j.issn.2096-109x.2017.00186 |
| work_keys_str_mv | AT zhengqiwangxiaobingfengchizhang studyofhighspeedmaliciouswebpagedetectionsystembasedontwostepclassifier |