M. Luckie, Alexander Marder, Marianne Fletcher, B. Huffaker, K. Claffy
{"title":"学习提取和使用主机名中的asn","authors":"M. Luckie, Alexander Marder, Marianne Fletcher, B. Huffaker, K. Claffy","doi":"10.1145/3419394.3423639","DOIUrl":null,"url":null,"abstract":"We present the design, implementation, evaluation, and validation of a system that learns regular expressions (regexes) to extract Autonomous System Numbers (ASNs) from hostnames associated with router interfaces. We train our system with ASNs inferred by Router-ToAsAssignment and bdrmapIT using topological constraints from traceroute paths, as well as ASNs recorded by operators in PeeringDB, to learn regexes for 206 different suffixes. Because these methods for inferring router ownership can infer the wrong ASN, we modify bdrmapIT to integrate this new capability to extract ASNs from hostnames. Evaluating against ground truth, our modification correctly distinguished stale from correct hostnames for 92.5% of hostnames with an ASN different from bdrmapIT's initial inference. This modification allowed bdrmapIT to increase the agreement between extracted and inferred ASNs for these routers in the January 2020 ITDK from 87.4% to 97.1% and reduce the error rate from 1/7.9 to 1/34.5. This work opens a broader horizon of opportunity for evidence-based router ownership inference.","PeriodicalId":255324,"journal":{"name":"Proceedings of the ACM Internet Measurement Conference","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Learning to Extract and Use ASNs in Hostnames\",\"authors\":\"M. Luckie, Alexander Marder, Marianne Fletcher, B. Huffaker, K. Claffy\",\"doi\":\"10.1145/3419394.3423639\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present the design, implementation, evaluation, and validation of a system that learns regular expressions (regexes) to extract Autonomous System Numbers (ASNs) from hostnames associated with router interfaces. We train our system with ASNs inferred by Router-ToAsAssignment and bdrmapIT using topological constraints from traceroute paths, as well as ASNs recorded by operators in PeeringDB, to learn regexes for 206 different suffixes. Because these methods for inferring router ownership can infer the wrong ASN, we modify bdrmapIT to integrate this new capability to extract ASNs from hostnames. Evaluating against ground truth, our modification correctly distinguished stale from correct hostnames for 92.5% of hostnames with an ASN different from bdrmapIT's initial inference. This modification allowed bdrmapIT to increase the agreement between extracted and inferred ASNs for these routers in the January 2020 ITDK from 87.4% to 97.1% and reduce the error rate from 1/7.9 to 1/34.5. This work opens a broader horizon of opportunity for evidence-based router ownership inference.\",\"PeriodicalId\":255324,\"journal\":{\"name\":\"Proceedings of the ACM Internet Measurement Conference\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-10-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the ACM Internet Measurement Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3419394.3423639\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the ACM Internet Measurement Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3419394.3423639","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
We present the design, implementation, evaluation, and validation of a system that learns regular expressions (regexes) to extract Autonomous System Numbers (ASNs) from hostnames associated with router interfaces. We train our system with ASNs inferred by Router-ToAsAssignment and bdrmapIT using topological constraints from traceroute paths, as well as ASNs recorded by operators in PeeringDB, to learn regexes for 206 different suffixes. Because these methods for inferring router ownership can infer the wrong ASN, we modify bdrmapIT to integrate this new capability to extract ASNs from hostnames. Evaluating against ground truth, our modification correctly distinguished stale from correct hostnames for 92.5% of hostnames with an ASN different from bdrmapIT's initial inference. This modification allowed bdrmapIT to increase the agreement between extracted and inferred ASNs for these routers in the January 2020 ITDK from 87.4% to 97.1% and reduce the error rate from 1/7.9 to 1/34.5. This work opens a broader horizon of opportunity for evidence-based router ownership inference.