![]() ![]() While on one hand the DNS protocol is relatively simple, the system has many moving parts, with multiple levels of caching and retries and replicated servers. The Internet's Domain Name System (DNS) is a frequent target of Distributed Denial-of-Service (DDoS) attacks, but such attacks have had very different outcomes-some attacks have disabled major public websites, while the external effects of other attacks have been minimal. We show that longer TTLs have significant promise in reducing latency, reducing it from 183 ms to 28.7 ms for one country-code TLD. ![]() We provide recommendations in TTL choice for different situations, and for where they must be configured. This paper provides the first careful evaluation of how these multiple, interacting factors affect the effective cache lifetimes of DNS records, and provides recommendations for how to configure DNS TTLs based on our findings. Exactly how TTL value choices affect operational networks is quite challenging to understand due to interactions across the distributed DNS service, where resolvers receive TTLs in different ways (answers and hints), TTLs are specified in multiple places (zones and their parent's glue), and while DNS resolution must be security-aware. Today there is relatively little guidance backed by research about how to set TTLs, and operators must balance conflicting demands of caching against agility of configuration. Finally, we introduce DNSRoute++, a new traceroute approach to understand the network infrastructure connecting transparent forwarders and resolvers.ĭNS depends on extensive caching for good performance, and every DNS zone owner must set Time-to-Live (TTL) values to control their DNS caching. Third, many transparent forwarders relay to a few selected public resolvers such as Google and Cloudflare, which confirms a consolidation trend of DNS stakeholders. In India alone, the ODNS consists of 80% transparent forwarders. Second, we find an increased deployment of transparent forwarders in Asia and South America. Unfortunately, common periodic scanning campaigns such as Shadowserver do not capture transparent forwarders and thus underestimate the current threat potential of the ODNS. First, transparent forwarders contribute 26% (563k) to the current ODNS infrastructure. In this short paper, we revisit the open DNS (ODNS) infrastructure and, for the first time, systematically measure and analyze transparent forwarders, DNS components that transparently relay between stub resolvers and recursive resolvers. Experimental results show that the proposed methods can identify and classify all kinds of DNS responses returned from open DNS resolvers. ![]() Among about 9 million responding open DNS resolvers in the experiments on the IPv4 address space, about 40% return unexpected DNS responses. Furthermore, an efficient identification and classification method is proposed to simplify the above process. Second, a classification method is proposed to classify unexpected DNS responses by their influences on clients and the Internet. First, an identification method is proposed to identify all kinds of DNS responses from each section of DNS messages. This paper explores unexpected DNS responses returned from open DNS resolvers in terms of identification and classification to better understand the behaviours of open DNS resolvers. Research on unexpected DNS responses is beneficial to the research, usage and management of open DNS resolvers. We call these DNS responses ‘unexpected DNS responses’. Previous research works show that DNS responses returned from some open DNS resolvers are not expected for clients and the Internet. Nowadays, the measurement of DNS resolvers, especially open DNS resolvers, has become a research focus. As the backbone of the domain name system (DNS), DNS resolvers are essential to the Internet. ![]()
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