DNS观测站:DNS的大图

Pawel Foremski, Oliver Gasser, G. Moura
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引用次数: 25

摘要

域名系统(DNS)被认为具有将域解析为IP地址的简单任务。由于它的存根解析器、不同层次的递归解析器、权威名称服务器、多种查询类型和DNSSEC, DNS生态系统实际上相当复杂。在本文中,我们介绍了一个新的流分析平台DNS Observatory,它提供了对DNS的鸟瞰。作为数据源,我们利用由数百个全球分布式探测器产生的大量被动DNS观察数据流,在递归解析器和权威名称服务器之间获得每秒200 k DNS查询的峰值。对于每个观察到的DNS交易,我们提取流量特征,汇总它们,并跟踪top-k DNS对象,例如,顶级权威域名服务器IP地址或顶级域。我们在四个月的时间里分析了1.6万亿DNS交易。这使我们能够描述DNS部署和流量模式,评估其相关的基础设施和性能,以及深入了解DNS和相关互联网协议的现代附加功能。我们发现了一个令人担忧的DNS流量集中:大约一半的观察到的流量仅由1 k权威名称服务器和10个AS运营商处理。通过评估DNS查询的中位数延迟,我们发现排名前10 k的域名服务器确实比不太受欢迎的域名服务器具有更短的响应时间,这与较少的路由器跳数相关。我们还研究了DNS TTL调整如何影响查询量,预测DNS基础设施即将发生的变化,以及负面缓存TTL如何影响Happy Eyeballs算法。我们发现一些受欢迎的域名由于短的负缓存ttl而占空DNS响应的份额高达90%。我们提出可行的措施来改进未发现的DNS缺陷。
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DNS Observatory: The Big Picture of the DNS
The Domain Name System (DNS) is thought of as having the simple-sounding task of resolving domains into IP addresses. With its stub resolvers, different layers of recursive resolvers, authoritative nameservers, a multitude of query types, and DNSSEC, the DNS ecosystem is actually quite complex. In this paper, we introduce DNS Observatory: a new stream analytics platform that provides a bird's-eye view on the DNS. As the data source, we leverage a large stream of passive DNS observations produced by hundreds of globally distributed probes, acquiring a peak of 200 k DNS queries per second between recursive resolvers and authoritative nameservers. For each observed DNS transaction, we extract traffic features, aggregate them, and track the top-k DNS objects, e.g., the top authoritative nameserver IP addresses or the top domains. We analyze 1.6 trillion DNS transactions over a four month period. This allows us to characterize DNS deployments and traffic patterns, evaluate its associated infrastructure and performance, as well as gain insight into the modern additions to the DNS and related Internet protocols. We find an alarming concentration of DNS traffic: roughly half of the observed traffic is handled by only 1 k authoritative nameservers and by 10 AS operators. By evaluating the median delay of DNS queries, we find that the top 10 k nameservers have indeed a shorter response time than less popular nameservers, which is correlated with less router hops. We also study how DNS TTL adjustments can impact query volumes, anticipate upcoming changes to DNS infrastructure, and how negative caching TTLs affect the Happy Eyeballs algorithm. We find some popular domains with a a share of up to 90 % of empty DNS responses due to short negative caching TTLs. We propose actionable measures to improve uncovered DNS shortcomings.
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