论文标题
基于云的大数据DNS分析
Cloud Based Big Data DNS Analytics at Turknet
论文作者
论文摘要
域名系统（DNS）是用于计算机，服务或连接到Internet的任何资源的层次分布式命名系统。 DNS将有关URL的查询解决到IP地址，目的是在全球范围内找到计算机服务和设备。截至目前，具有大量DNS数据的分析应用是一个具有挑战性的问题。由于数据表征的敏感性，从DNS数据中聚集了来自DNS数据的域流量的特征，因此需要更复杂的分析平台和工具。在这项研究中，提出了基于Apache Spark，基于DNS数据的基于云的大数据应用程序，以及基于流量的定期趋势模式，以通过其查询流量时间序列的特征将许多域名和区域分为单独的组。通过商业智能应用程序讨论了每日操作中的Turknet DNS数据的初步实验结果。
Domain Name System (DNS) is a hierarchical distributed naming system for computers, services, or any resource connected to the Internet. A DNS resolves queries for URLs into IP addresses for the purpose of locating computer services and devices worldwide. As of now, analytical applications with a vast amount of DNS data are a challenging problem. Clustering the features of domain traffic from a DNS data has given necessity to the need for more sophisticated analytics platforms and tools because of the sensitivity of the data characterization. In this study, a cloud based big data application, based on Apache Spark, on DNS data is proposed, as well as a periodic trend pattern based on traffic to partition numerous domain names and region into separate groups by the characteristics of their query traffic time series. Preliminary experimental results on a Turknet DNS data in daily operations are discussed with business intelligence applications.
