A. Menshchikov, A. Komarova, Y. Gatchin, A. Korobeynikov, Nina Tishukova
{"title":"对不同网络爬虫行为的研究","authors":"A. Menshchikov, A. Komarova, Y. Gatchin, A. Korobeynikov, Nina Tishukova","doi":"10.23919/FRUCT.2017.8071322","DOIUrl":null,"url":null,"abstract":"The article deals with a study of web-crawler behaviour on different websites. A classification of web-robots, information gathering tools and their detection methods are provided. Well-known scrapers and their behaviour are analyzed on the base of large web-server log set. Experimental results demonstrate that web-robot can be distinguished from human by feature analysis. The results of the research can be used as a basis for comprehensive intrusion detection and prevention system development.","PeriodicalId":114353,"journal":{"name":"2017 20th Conference of Open Innovations Association (FRUCT)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"A study of different web-crawler behaviour\",\"authors\":\"A. Menshchikov, A. Komarova, Y. Gatchin, A. Korobeynikov, Nina Tishukova\",\"doi\":\"10.23919/FRUCT.2017.8071322\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The article deals with a study of web-crawler behaviour on different websites. A classification of web-robots, information gathering tools and their detection methods are provided. Well-known scrapers and their behaviour are analyzed on the base of large web-server log set. Experimental results demonstrate that web-robot can be distinguished from human by feature analysis. The results of the research can be used as a basis for comprehensive intrusion detection and prevention system development.\",\"PeriodicalId\":114353,\"journal\":{\"name\":\"2017 20th Conference of Open Innovations Association (FRUCT)\",\"volume\":\"39 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 20th Conference of Open Innovations Association (FRUCT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23919/FRUCT.2017.8071322\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 20th Conference of Open Innovations Association (FRUCT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/FRUCT.2017.8071322","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The article deals with a study of web-crawler behaviour on different websites. A classification of web-robots, information gathering tools and their detection methods are provided. Well-known scrapers and their behaviour are analyzed on the base of large web-server log set. Experimental results demonstrate that web-robot can be distinguished from human by feature analysis. The results of the research can be used as a basis for comprehensive intrusion detection and prevention system development.
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