{"title":"A Nameserver Importance Ranking Method Based on Heterogeneous Information Network","authors":"Bingyang Guo, M. Zhang, Chengxi Xu, Fan Shi","doi":"10.1109/ICCCS52626.2021.9449288","DOIUrl":null,"url":null,"abstract":"As the Internet continues to evolve, the Domain Name System (DNS), which is originally designated as distributed service, starts to aggregate to fewer DNS servers. Thus, it is of great significance to dig out these name servers and carry out specific security protection on them. Researchers try to calculate the importance of an individual name server based on the number of domains resolved by it. However, we argue that semantic information such as the structure of a name server can also contribute to its importance. In this paper, we present a novel ranking method based on heterogeneous information networks, which not only considers the number of zones affected by the nameserver but also takes the importance of the zone and the influence of its adjacent name servers into consideration. We collect the name servers of the Alexa Top 1000 domains and calculate their importance. Results show that our method is more accurate compared to the existing method.","PeriodicalId":376290,"journal":{"name":"2021 IEEE 6th International Conference on Computer and Communication Systems (ICCCS)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE 6th International Conference on Computer and Communication Systems (ICCCS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCCS52626.2021.9449288","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
As the Internet continues to evolve, the Domain Name System (DNS), which is originally designated as distributed service, starts to aggregate to fewer DNS servers. Thus, it is of great significance to dig out these name servers and carry out specific security protection on them. Researchers try to calculate the importance of an individual name server based on the number of domains resolved by it. However, we argue that semantic information such as the structure of a name server can also contribute to its importance. In this paper, we present a novel ranking method based on heterogeneous information networks, which not only considers the number of zones affected by the nameserver but also takes the importance of the zone and the influence of its adjacent name servers into consideration. We collect the name servers of the Alexa Top 1000 domains and calculate their importance. Results show that our method is more accurate compared to the existing method.
随着互联网的不断发展,原本被指定为分布式服务的DNS (Domain Name System)开始向更少的DNS服务器聚合。因此,挖掘这些域名服务器并对其进行针对性的安全保护具有重要意义。研究人员试图根据域名服务器解析的域名数量来计算单个域名服务器的重要性。然而,我们认为语义信息,如名称服务器的结构,也有助于其重要性。本文提出了一种基于异构信息网络的域名排序方法,该方法不仅考虑了受域名服务器影响的区域数量,而且考虑了区域的重要性及其相邻域名服务器的影响。我们收集了Alexa Top 1000域名的域名服务器,并计算了它们的重要性。结果表明,与现有方法相比,该方法具有更高的精度。