DNSOP Working Group G. Moura
Internet-Draft SIDN Labs/TU Delft
Intended status: Informational W. Hardaker
Expires: September 12, 2019 J. Heidemann
USC/Information Sciences Institute
M. Davids
SIDN Labs
March 11, 2019
Recommendations for Authoritative Servers Operators
draft-moura-dnsop-authoritative-recommendations-03
Abstract
This document summarizes recent research work exploring DNS
configurations and offers specific, tangible recommendations to
operators for configuring authoritative servers.
This document is not an Internet Standards Track specification; it is
published for informational purposes.
Ed note
Text inside square brackets ([RF:ABC]) refers to individual comments
we have received about the draft, and enumerated under
<https://github.com/gmmoura/draft-moura-dnsop-authoritative-
recommendations/blob/master/reviews/reviews-dnsop.md>. They will be
removed before publication.
This draft is being hosted on GitHub - <https://github.com/gmmoura/
draft-moura-dnsop-authoritative-recommendations>, where the most
recent version of the document and open issues can be found. The
authors gratefully accept pull requests.
Status of This Memo
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This Internet-Draft will expire on September 12, 2019.
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Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 2
2. R1: Use equaly strong IP anycast in every authoritative
server to achieve even load distribution . . . . . . . . . . 4
3. R2: Routing Can Matter More Than Locations . . . . . . . . . 6
4. R3: Collecting Detailed Anycast Catchment Maps Ahead of
Actual Deployment Can Improve Engineering Designs . . . . . . 6
5. R4: When under stress, employ two strategies . . . . . . . . 8
6. R5: Consider longer time-to-live values whenever possible . . 9
7. R6: Shared Infrastructure Risks Collateral Damage During
Attacks . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
8. Security considerations . . . . . . . . . . . . . . . . . . . 12
9. Privacy Considerations . . . . . . . . . . . . . . . . . . . 12
10. IANA considerations . . . . . . . . . . . . . . . . . . . . . 12
11. Acknowledgements . . . . . . . . . . . . . . . . . . . . . . 12
12. References . . . . . . . . . . . . . . . . . . . . . . . . . 13
12.1. Normative References . . . . . . . . . . . . . . . . . . 13
12.2. Informative References . . . . . . . . . . . . . . . . . 14
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 16
1. Introduction
The domain name system (DNS) has main two types of DNS servers:
authoritative servers and recursive resolvers. Figure 1 shows their
relationship. An authoritative server (ATn in Figure 1) knows the
content of a DNS zone from local knowledge, and thus can answer
queries about that zone without needing to query other servers
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[RFC2181]. A recursive resolver (Re_n) is a program that extracts
information from name servers in response to client requests
[RFC1034]. A client (stub in Figure 1) refers to stub resolver
[RFC1034] that is typically located within the client software.
+-----+ +-----+ +-----+ +-----+
| AT1 | | AT2 | | AT3 | | AT4 |
+-----+ +-----+ +-----+ +-----+
^ ^ ^ ^
| | | |
| +-----+ | |
+------|Re_1 |------+ |
| +-----+ |
| ^ |
| | |
| +-----+ +-----+ |
+------|Re_2 | |Re_3 |-----+
+-----+ +-----+
^ ^
| |
| +------+ |
+-| stub |--+
+------+
Figure 1: Relationship between recursive resolvers (Re_n) and
authoritative name servers (ATn)
DNS queries/responses contribute to user's perceived latency and
affect user experience [Sigla2014], and the DNS system has been
subject to repeated Denial of Service (DoS) attacks (for example, in
November 2015 [Moura16b]) in order to degrade user experience.
To reduce latency and improve resiliency against DoS attacks, DNS
uses several types of server replication. Replication at the
authoritative server level can be achieved with (i) the deployment of
multiple servers for the same zone [RFC1035] (AT1--AT4 in Figure 1),
(ii) the use of IP anycast [RFC1546][RFC4786][RFC7094] that allows
the same IP address to be announced from multiple locations (each of
them referred to as anycast instance [RFC8499]) and (iii) by using
load balancers to support multiple servers inside a single
(potentially anycasted) instance. As a consequence, there are many
possible ways an authoritative DNS provider can engineer its
production authoritative server network, with multiple viable choices
and no single optimal design.
This document summarizes recent research work exploring DNS
configurations and offers specific tangible recommendations to DNS
authoritative servers operators (DNS operators hereafter).
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[RF:JAb2]], [RF:MSJ1], [RF:DW2]. The recommendations (R1-R6)
presented in this document are backed by previous research work,
which used wide-scale Internet measurements upon which to draw their
conclusions. This document describes the key engineering options,
and points readers to the pertinent papers for details.
[RF:JAb1, Issue#2]. These recommendations are designed for operators
of "large" authoritative servers for domains like TLDs. "Large"
authoritative servers refers to those with a significant global user
population. These recommendations may not be appropriate for smaller
domains, such as those used by an organization with users in one city
or region, where goals such as uniform low latency are less strict.
It is likely that these recommendations might be useful in a wider
context, such as for any stateless/short-duration, anycasted service.
Because the conclusions of the studies don't verify this fact, the
wording in this document discusses DNS authoritative services only.
2. R1: Use equaly strong IP anycast in every authoritative server to
achieve even load distribution
Authoritative DNS servers operators announce their authoritative
servers as NS records[RFC1034]. Different authoritatives for a given
zone should return the same content, typically by staying
synchronized using DNS zone transfers (AXFR[RFC5936] and
IXFR[RFC1995]) to coordinate the authoritative zone data to return to
their clients.
DNS heavily relies upon replication to support high reliability,
capacity and to reduce latency [Moura16b]. DNS has two complementary
mechanisms to replicate the service. First, the protocol itself
supports nameserver replication of DNS service for a DNS zone through
the use of multiple nameservers that each operate on different IP
addresses, listed by a zone's NS records. Second, each of these
network addresses can run from multiple physical locations through
the use of IP anycast[RFC1546][RFC4786][RFC7094], by announcing the
same IP address from each instance and allowing Internet routing
(BGP[RFC4271]) to associate clients with their topologically nearest
anycast instance. Outside the DNS protocol, replication can be
achieved by deploying load balancers at each physical location.
Nameserver replication is recommended for all zones (multiple NS
records), and IP anycast is used by most large zones such as the DNS
Root, most top-level domains[Moura16b] and large commercial
enterprises, governments and other organizations.
Most DNS operators strive to reduce latency for users of their
service. However, because they control only their authoritative
servers, and not the recursive resolvers communicating with those
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servers, it is difficult to ensure that recursives will be served by
the closest authoritative server. Server selection is up to the
recursive resolver's software implementation, and different software
vendors and releases employ different criteria to chose which
authoritative servers with which to communicate.
Knowing how recursives choose authoritative servers is a key step to
better engineer the deployment of authoritative servers.
[Mueller17b] evaluates this with a measurement study in which they
deployed seven unicast authoritative name servers in different global
locations and queried these authoritative servers from more than 9k
RIPE Atlas probes and and their respective recursive resolvers.
In the wild, [Mueller17b] found that recursives query all available
authoritative servers, regardless of the observed latency. But the
distribution of queries tend to be skewed towards authoritatives with
lower latency: the lower the latency between a recursive resolver and
an authoritative server, the more often the recursive will send
queries to that authoritative. These results were obtained by
aggregating results from all vantage points and not specific to any
vendor/version.
The hypothesis is that this behavior is a consequence of two main
criteria employed by resolvers when choosing authoritatives:
performance (lower latency) and diversity of authoritatives, where a
resolver checks all authoritative servers to determine which is
closer and to provide alternatives if one is unavailable.
For a DNS operator, this policy means that latency of all
authoritatives matter, so all must be similarly capable, since all
available authoritatives will be queried by most recursive resolvers.
Since unicast cannot deliver good latency worldwide (a unicast
authoritative server in Europe will always have high latency to
resolvers in California, for example, given its geographical
distance), [Mueller17b] recommends to DNS operators that they deploy
equally strong IP anycast in every authoritative server (NS record),
in terms of number of instances and peering, and, consequently, to
phase out unicast, so they can deliver latency values to global
clients. However, [Mueller17b] also notes that DNS operators should
also take architectural considerations into account when planning for
deploying anycast [RFC1546].
This recommendation was deployed at the ".nl" TLD zone, which
originally had seven authoritative severs (mixed unicast/anycast
setup). .nl has moved in early 2018 to a setup with 4 anycast
authoritative name servers. This is not to say that .nl was the
first - other zones, have been running anycast only authoritatives
(e.g., .be since 2013). [Mueller17b] contribution is to show that
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unicast cannot deliver good latency worldwide, and that anycast has
to be deployed to deliver good latency worldwide.
3. R2: Routing Can Matter More Than Locations
A common metric when choosing an anycast DNS provider or setting up
an anycast service is the number of anycast instances[RFC4786], i.e.,
the number of global locations from which the same address is
announced with BGP. Intuitively, one could think that more instances
will lead to shorter response times.
However, this is not necessarily true. In fact, [Schmidt17a] found
that routing can matter more than the total number of locations.
They analyzed the relationship between the number of anycast
instances and the performance of a service (latency-wise, RTT) and
measured the overall performance of four DNS Root servers, namely C,
F, K and L, from more than 7.9k RIPE Atlas probes.
[Schmidt17a] found that C-Root, a smaller anycast deployment
consisting of only 8 instances (they refer to anycast instance as
anycast site), provided a very similar overall performance than that
of the much larger deployments of K and L, with 33 and 144 instances
respectively. The median RTT for C, K and L Root was between
30-32ms.
[Schmidt17a] recommendation for DNS operators when engineering
anycast services is consider factors other than just the number of
instances (such as local routing connectivity) when designing for
performance. They showed that 12 instances can provide reasonable
latency, given they are globally distributed and have good local
interconnectivity. However, more instances can be useful for other
reasons, such as when handling DDoS attacks [Moura16b].
4. R3: Collecting Detailed Anycast Catchment Maps Ahead of Actual
Deployment Can Improve Engineering Designs
An anycast DNS service may have several dozens or even more than one
hundred instances (such as L-Root does). Anycast leverages Internet
routing to distribute the incoming queries to a service's distributed
anycast instances; in theory, BGP (the Internet's defacto routing
protocol) forwards incoming queries to a nearby anycast instance (in
terms of BGP distance). However, usually queries are not evenly
distributed across all anycast instances, as found in the case of
L-Root [IcannHedge18].
Adding new instances to an anycast service may change the load
distribution across all instances, leading to suboptimal usage of the
service or even stressing some instances while others remain
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underutilized. This is a scenario that operators constantly face
when expanding an anycast service. Besides, when setting up a new
anycast service instance, operators cannot directly estimate the
query distribution among the instances in advance of enabling the new
instance.
To estimate the query loads across instances of an expanding service
or a when setting up an entirely new service, operators need detailed
anycast maps and catchment estimates (i.e., operators need to know
which prefixes will be matched to which anycast instance). To do
that, [Vries17b] developed a new technique enabling operators to
carry out active measurements, using aan open-source tool called
Verfploeter (available at [VerfSrc]). Verfploeter maps a large
portion of the IPv4 address space, allowing DNS operators to predict
both query distribution and clients catchment before deploying new
anycast instances.
[Vries17b] shows how this technique was used to predict both the
catchment and query load distribution for the new anycast service of
B-Root. Using two anycast instances in Miami (MIA) and Los Angeles
(LAX) from the operational B-Root server, they sent ICMP echo packets
to IP addresses to each IPv4 /24 on the Internet using a source
address within the anycast prefix. Then, they recorded which
instance the ICMP echo replies arrived at based on the Internet's BGP
routing. This analysis resulted in an Internet wide catchment map.
Weighting was then applied to the incoming traffic prefixes based on
of 1 day of B-Root traffic (2017-04-12, DITL datasets [Ditl17]). The
combination of the created catchment mapping and the load per prefix
created an estimate predicting that 81.6% of the traffic would go to
the LAX instance. The actual value was 81.4% of traffic going to
LAX, showing that the estimation was pretty close and the Verfploeter
technique was a excellent method of predicting traffic loads in
advance of a new anycast instance deployment ([Vries17b] also uses
the term anycast site to refer to anycast instance).
Besides that, Verfploeter can also be used to estimate how traffic
shifts among instances when BGP manipulations are executed, such as
AS Path prepending that is frequently used by production networks
during DDoS attacks. A new catchment mapping for each prepending
configuration configuration: no prepending, and prepending with 1, 2
or 3 hops at each instance. Then, [Vries17b] shows that this mapping
can accurately estimate the load distribution for each configuration.
An important operational takeaway from [Vries17b] is that DNS
operators can make informed choices when engineering new anycast
instances or when expending new ones by carrying out active
measurements using Verfploeter in advance of operationally enabling
the fully anycast service. Operators can spot sub-optimal routing
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situations early, with a fine granularity, and with significantly
better coverage than using traditional measurement platforms such as
RIPE Atlas.
To date, Verfploeter has been deployed on B-Root[Vries17b], on a
operational testbed (Anycast testbed) [AnyTest], and on a large
unnamed operator.
The recommendation is therefore to deploy a small test Verfploeter-
enabled platform in advance at a potential anycast instance may
reveal the realizable benefits of using that instance as an anycast
interest, potentially saving significant financial and labor costs of
deploying hardware to a new instance that was less effective than as
had been hoped.
5. R4: When under stress, employ two strategies
DDoS attacks are becoming bigger, cheaper, and more frequent
[Moura16b]. The most powerful recorded DDoS attack to DNS servers to
date reached 1.2 Tbps, by using IoT devices [Perlroth16]. Such
attacks call for an answer for the following question: how should a
DNS operator engineer its anycast authoritative DNS server react to
the stress of a DDoS attack? This question is investigated in study
[Moura16b] in which empirical observations are grounded with the
following theoretical evaluation of options.
An authoritative DNS server deployed using anycast will have many
server instances distributed over many networks and instances.
Ultimately, the relationship between the DNS provider's network and a
client's ISP will determine which anycast instance will answer
queries for a given client. As a consequence, when an anycast
authoritative server is under attack, the load that each anycast
instance receives is likely to be unevenly distributed (a function of
the source of the attacks), thus some instances may be more
overloaded than others which is what was observed analyzing the Root
DNS events of Nov. 2015 [Moura16b]. Given the fact that different
instances may have different capacity (bandwidth, CPU, etc.), making
a decision about how to react to stress becomes even more difficult.
In practice, an anycast instance under stress, overloaded with
incoming traffic, has two options:
o It can withdraw or pre-prepend its route to some or to all of its
neighbors, ([RF:Issue3]) perform other traffic shifting tricks
(such as reducing the propagation of its announcements using BGP
communities[RFC1997]) which shrinks portions of its catchment),
use FlowSpec [RFC5575] or other upstream communication mechanisms
to deploy upstream filtering. The goals of these techniques is to
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perform some combination of shifting of both legitimate and attack
traffic to other anycast instances (with hopefully greater
capacity) or to block the traffic entirely.
o Alternatively, it can be become a degraded absorber, continuing to
operate, but with overloaded ingress routers, dropping some
incoming legitimate requests due to queue overflow. However,
continued operation will also absorb traffic from attackers in its
catchment, protecting the other anycast instances.
[Moura16b] saw both of these behaviors in practice in the Root DNS
events, observed through instance reachability and route-trip time
(RTTs). These options represent different uses of an anycast
deployment. The withdrawal strategy causes anycast to respond as a
waterbed, with stress displacing queries from one instance to others.
The absorption strategy behaves as a conventional mattress,
compressing under load, with some queries getting delayed or dropped.
Although described as strategies and policies, these outcomes are the
result of several factors: the combination of operator and host ISP
routing policies, routing implementations withdrawing under load, the
nature of the attack, and the locations of the instances and the
attackers. Some policies are explicit, such as the choice of local-
only anycast instances, or operators removing an instance for
maintenance or modifying routing to manage load. However, under
stress, the choices of withdrawal and absorption can also be results
that emerge from a mix of explicit choices and implementation
details, such as BGP timeout values.
[Moura16b] speculates that more careful, explicit, and automated
management of policies may provide stronger defenses to overload, an
area currently under study. For DNS operators, that means that
besides traditional filtering, two other options are available
(withdraw/prepend/communities or isolate instances), and the best
choice depends on the specifics of the attack.
Note that this recommendation refers to the operation of one anycast
service, i.e., one anycast NS record. However, DNS zones with
multiple NS anycast services may expect load to spill from one
anycast server to another,as resolvers switch from authoritative to
authoritative when attempting to resolve a name [Mueller17b].
6. R5: Consider longer time-to-live values whenever possible
In a DNS response, each resource record is accompanied by a time-to-
live value (TTL), which "describes how long a RR can be cached before
it should be discarded" [RFC1034]. The TTL values are set by zone
owners in their zone files - either specifically per record or by
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using default values for the entire zone. Sometimes the same
resource record may have different TTL values - one from the parent
and one from the child DNS server. In this case, resolvers are
expected to prioritize the answer according to Section 5.4.1 in
[RFC2181].
While set at authoritative servers, (ATn in Figure 1), the TTL value
in fact influences the behavior of recursive resolvers (and their
operators - "Re_n" in the same figure), by setting an upper limit on
how long a record should be cached before discarded. In this sense,
caching can be seen as a sort of "ephemeral replication", i.e., the
contents of an authoritative server are placed at a recursive
resolver cache for a period of time up to the TTL value. Caching
improves response times by avoiding repeated queries between
recursive resolvers and authoritative.
Besides improving performance, it has been argued that caching plays
a significant role in protecting users during DDoS attacks against
authoritative servers. To investigate that, [Moura18b] evaluates the
role of caching (and retries) in DNS resiliency to DDoS attacks. Two
authoritative servers were configured for a newly registered domain
and a series of experiments were carried out using various TTL values
(60,1800, 3600, 86400s) for records. Unique DNS queries were sent
from roughly 15,000 vantage points, using RIPE Atlas.
[Moura18b] found that, under normal operations, caching works as
expected 70% of the times in the wild. It is believed that complex
recursive infrastructure (such as anycast recursives with fragmented
cache), besides cache flushing and hierarchy explains these other 30%
of the non-cached records. The results from the experiments were
confirmed by analyzing authoritative traffic for the .nl TLD, which
showed similar figures.
[Moura18b] also emulated DDoS attacks on authoritative servers by
dropping all incoming packets for various TTLs values. For
experiments when all authoritative servers were completely
unreachable, they found that the TTL value on the DNS records
determined how long clients received responses, together with the
status of the cache at the attack time. Given the TTL value
decreases as time passes at the cache, it protected clients for up to
its value in cache. Once the TTL expires, there was some evidence of
some recursives serving stale content [I-D.ietf-dnsop-serve-stale].
Serving stale is the only viable option when TTL values expire in
recursive caches and authoritative servers became completely
unavailable.
They also emulated partial-failure DDoS, i.e., DDoS that cause
authoritative to respond to be able to respond part of the queries
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(similar to Dyn 2016 [Perlroth16]). They emulate such scenario by
dropping incoming packet at rates of 50-90%, for various TTL values.
They found that:
o Caching was a key component in the success of queries. For
example, with a 50% packet drop rate at the authoritatives, most
clients eventually got an answer.
o Recursives retries was also a key part of resilience: when caching
could not help (for a scenario with TTL of 60s, and time in
between probing of 10 minutes), recursive servers kept retrying
queries to authoritatives. With 90% packet drop on both
authoritatives (with TTL of 60s), 27% of clients still got an
answer due to retries, at the price of increased response times.
However, this came with a price for authroritative servers: a 8.1
times increase in normal traffic during a 90% packet drop with TTL
of 60s, as recursives attempt to resolve queries - thus
effectively creating "friendly fire".
Altogether, these results help to explain why previous attacks
against the Roots were not noticed by most users [Moura18b] and why
other attacks (such as Dyn 2016 [Perlroth16]) had significant impact
on users experience: records on the Root zone have TTL values ranging
from 1 to 6 days, while some of unreachable Dyn clients had TTL
values ranging from 120 to 300s, which limit how long records ought
to be cached.
Therefore, given the important role of the TTL on user's experience
during a DDoS attack (and in reducing ''friendly fire''), it is
recommended that DNS zone owners set their TTL values carefully,
using reasonable TTL values (at least 1 hour) whenever possible,
given its role in DNS resilience against DDoS attacks. However, the
choice of the value depends on the specifics of each operator (CDNs
are known for using TTL values in the range of few minutes). The
drawback of setting larger TTL values is that changes on the
authoritative system infrastructure (e.g.: adding a new authoritative
server or changing IP address) will take at least as long as the TTL
to propagate among clients.
7. R6: Shared Infrastructure Risks Collateral Damage During Attacks
Co-locating services, such as authoritative servers, creates some
degree of shared risk, in that stress on one service may spill over
into another, resulting in collateral damage. Collateral damage is a
common side-effect of DDoS, and data centers and operators strive to
minimize collateral damage through redundancy, overcapacity, and
isolation.
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This has been seen in practice during the DDoS attack against the
Root DNS system in November 2015 [Moura16b]. In this study, it was
shown that two services not directly targeted by the attack, namely
D-Root and the .nl TLD, suffered collateral damage. These services
showed reduced end-to-end performance (i.e., higher latency and
reduced reachability) with timing consistent with the DDoS event,
strongly suggesting a shared resource with original targets of the
attack.
Another example of collateral damage was the 1.2 Tbps attack against
Dyn, a major DNS provider on October 2017 [Perlroth16]. As a result,
many of their customers, including Airbnb, HBO, Netflix, and Twitter
experienced issues with clients failing to resolve their domains,
since the servers partially shared the same infrastructure.
It is recommended, therefore, when choosing third-party DNS
providers, operators should be aware of shared infrastructure risks.
By sharing infrastructure, there is an increased attack surface.
8. Security considerations
This document suggests the use of [I-D.ietf-dnsop-serve-stale]. It
be noted that usage of such methods may affect data integrity of DNS
information. This document describes methods of mitigating changes
of a denial of service threat within a DNS service.
As this document discusses research, there are no further security
considerations, other than the ones mentioned in the normative
references.
9. Privacy Considerations
This document does not add any practical new privacy issues.
10. IANA considerations
This document has no IANA actions.
11. Acknowledgements
This document is a summary of the main recommendations of five
research works referred in this document. As such, they were only
possible thanks to the hard work of the authors of these research
works.
The authors of this document are also co-authors of these research
works. However, not all thirteen authors of these research papers
are also authors of this document. We would like to thank those not
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included in this document's author list for their work: Ricardo de O.
Schmidt, Wouter B de Vries, Moritz Mueller, Lan Wei, Cristian
Hesselman, Jan Harm Kuipers, Pieter-Tjerk de Boer and Aiko Pras.
We would like also to thank the various reviewers of different
versions of this draft: Duane Wessels, Joe Abley, Toema Gavrichenkov,
John Levine, Michael StJohns, Kristof Tuyteleers, and Stefan Ubbink.
Besides those, we would like thank those who have been individually
thanked in each research work, RIPE NCC and DNS OARC for their tools
and datasets used in this research, as well as the funding agencies
sponsoring the individual research works.
12. References
12.1. Normative References
[I-D.ietf-dnsop-serve-stale]
Lawrence, D., Kumari, W., and P. Sood, "Serving Stale Data
to Improve DNS Resiliency", draft-ietf-dnsop-serve-
stale-03 (work in progress), February 2019.
[RFC1034] Mockapetris, P., "Domain names - concepts and facilities",
STD 13, RFC 1034, DOI 10.17487/RFC1034, November 1987,
<https://www.rfc-editor.org/info/rfc1034>.
[RFC1035] Mockapetris, P., "Domain names - implementation and
specification", STD 13, RFC 1035, DOI 10.17487/RFC1035,
November 1987, <https://www.rfc-editor.org/info/rfc1035>.
[RFC1546] Partridge, C., Mendez, T., and W. Milliken, "Host
Anycasting Service", RFC 1546, DOI 10.17487/RFC1546,
November 1993, <https://www.rfc-editor.org/info/rfc1546>.
[RFC1995] Ohta, M., "Incremental Zone Transfer in DNS", RFC 1995,
DOI 10.17487/RFC1995, August 1996,
<https://www.rfc-editor.org/info/rfc1995>.
[RFC1997] Chandra, R., Traina, P., and T. Li, "BGP Communities
Attribute", RFC 1997, DOI 10.17487/RFC1997, August 1996,
<https://www.rfc-editor.org/info/rfc1997>.
[RFC2181] Elz, R. and R. Bush, "Clarifications to the DNS
Specification", RFC 2181, DOI 10.17487/RFC2181, July 1997,
<https://www.rfc-editor.org/info/rfc2181>.
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[RFC4271] Rekhter, Y., Ed., Li, T., Ed., and S. Hares, Ed., "A
Border Gateway Protocol 4 (BGP-4)", RFC 4271,
DOI 10.17487/RFC4271, January 2006,
<https://www.rfc-editor.org/info/rfc4271>.
[RFC4786] Abley, J. and K. Lindqvist, "Operation of Anycast
Services", BCP 126, RFC 4786, DOI 10.17487/RFC4786,
December 2006, <https://www.rfc-editor.org/info/rfc4786>.
[RFC5575] Marques, P., Sheth, N., Raszuk, R., Greene, B., Mauch, J.,
and D. McPherson, "Dissemination of Flow Specification
Rules", RFC 5575, DOI 10.17487/RFC5575, August 2009,
<https://www.rfc-editor.org/info/rfc5575>.
[RFC5936] Lewis, E. and A. Hoenes, Ed., "DNS Zone Transfer Protocol
(AXFR)", RFC 5936, DOI 10.17487/RFC5936, June 2010,
<https://www.rfc-editor.org/info/rfc5936>.
[RFC7094] McPherson, D., Oran, D., Thaler, D., and E. Osterweil,
"Architectural Considerations of IP Anycast", RFC 7094,
DOI 10.17487/RFC7094, January 2014,
<https://www.rfc-editor.org/info/rfc7094>.
[RFC8499] Hoffman, P., Sullivan, A., and K. Fujiwara, "DNS
Terminology", BCP 219, RFC 8499, DOI 10.17487/RFC8499,
January 2019, <https://www.rfc-editor.org/info/rfc8499>.
12.2. Informative References
[AnyTest] Schmidt, R., "Anycast Testbed", December 2018,
<http://www.anycast-testbed.com/>.
[Ditl17] OARC, D., "2017 DITL data", October 2018,
<https://www.dns-oarc.net/oarc/data/ditl/2017>.
[IcannHedge18]
ICANN, ., "DNS-STATS - Hedgehog 2.4.1", October 2018,
<http://stats.dns.icann.org/hedgehog/>.
[Moura16b]
Moura, G., Schmidt, R., Heidemann, J., Mueller, M., Wei,
L., and C. Hesselman, "Anycast vs DDoS Evaluating the
November 2015 Root DNS Events.", ACM 2016 Internet
Measurement Conference, DOI /10.1145/2987443.2987446,
October 2016,
<https://www.isi.edu/~johnh/PAPERS/Moura16b.pdf>.
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[Moura18b]
Moura, G., Heidemann, J., Mueller, M., Schmidt, R., and M.
Davids, "When the Dike Breaks: Dissecting DNS Defenses
During DDos", ACM 2018 Internet Measurement Conference,
DOI 10.1145/3278532.3278534, October 2018,
<https://www.isi.edu/~johnh/PAPERS/Moura18b.pdf>.
[Mueller17b]
Mueller, M., Moura, G., Schmidt, R., and J. Heidemann,
"Recursives in the Wild- Engineering Authoritative DNS
Servers.", ACM 2017 Internet Measurement Conference,
DOI 10.1145/3131365.3131366, October 2017,
<https://www.isi.edu/%7ejohnh/PAPERS/Mueller17b.pdf>.
[Perlroth16]
Perlroth, N., "Hackers Used New Weapons to Disrupt Major
Websites Across U.S.", October 2016,
<https://www.nytimes.com/2016/10/22/business/
internet-problems-attack.html>.
[Schmidt17a]
Schmidt, R., Heidemann, J., and J. Kuipers, "Anycast
Latency - How Many Sites Are Enough. In Proceedings of the
Passive and Active Measurement Workshop", PAM Passive and
Active Measurement Conference, March 2017,
<https://www.isi.edu/%7ejohnh/PAPERS/Schmidt17a.pdf>.
[Sigla2014]
Singla, A., Chandrasekaran, B., Godfrey, P., and B. Maggs,
"The Internet at the speed of light. In Proceedings of the
13th ACM Workshop on Hot Topics in Networks (Oct 2014)",
ACM Workshop on Hot Topics in Networks, October 2014,
<http://speedierweb.web.engr.illinois.edu/cspeed/papers/
hotnets14.pdf>.
[VerfSrc] Vries, W., "Verfploeter source code", November 2018,
<https://github.com/Woutifier/verfploeter>.
[Vries17b]
Vries, W., Schmidt, R., Hardaker, W., Heidemann, J., Boer,
P., and A. Pras, "Verfploeter - Broad and Load-Aware
Anycast Mapping", ACM 2017 Internet Measurement
Conference, DOI 10.1145/3131365.3131371, October 2017,
<https://www.isi.edu/%7ejohnh/PAPERS/Vries17b.pdf>.
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Authors' Addresses
Giovane C. M. Moura
SIDN Labs/TU Delft
Meander 501
Arnhem 6825 MD
The Netherlands
Phone: +31 26 352 5500
Email: giovane.moura@sidn.nl
Wes Hardaker
USC/Information Sciences Institute
PO Box 382
Davis 95617-0382
U.S.A.
Phone: +1 (530) 404-0099
Email: ietf@hardakers.net
John Heidemann
USC/Information Sciences Institute
4676 Admiralty Way
Marina Del Rey 90292-6695
U.S.A.
Phone: +1 (310) 448-8708
Email: johnh@isi.edu
Marco Davids
SIDN Labs
Meander 501
Arnhem 6825 MD
The Netherlands
Phone: +31 26 352 5500
Email: marco.davids@sidn.nl
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