A Survey of Worldwide Censorship Techniques
draft-irtf-pearg-censorship-02
The information below is for an old version of the document.
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This is an older version of an Internet-Draft that was ultimately published as RFC 9505.
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| Authors | Joseph Lorenzo Hall , Michael D. Aaron , Stan Adams , Amelia Andersdotter , Ben Jones , Nick Feamster | ||
| Last updated | 2020-03-09 | ||
| Replaces | draft-hall-censorship-tech | ||
| RFC stream | Internet Research Task Force (IRTF) | ||
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draft-irtf-pearg-censorship-02
pearg J. Hall
Internet-Draft Internet Society
Intended status: Informational M. Aaron
Expires: September 10, 2020 CU Boulder
S. Adams
CDT
A. Andersdotter
B. Jones
Princeton
N. Feamster
U Chicago
March 09, 2020
A Survey of Worldwide Censorship Techniques
draft-irtf-pearg-censorship-02
Abstract
This document describes the technical mechanisms used by censorship
regimes around the world to block or impair Internet traffic. It
aims to make designers, implementers, and users of Internet protocols
aware of the properties being exploited and mechanisms used to censor
end-user access to information. This document makes no suggestions
on individual protocol considerations, and is purely informational,
intended to be a reference.
Status of This Memo
This Internet-Draft is submitted in full conformance with the
provisions of BCP 78 and BCP 79.
Internet-Drafts are working documents of the Internet Engineering
Task Force (IETF). Note that other groups may also distribute
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Drafts is at https://datatracker.ietf.org/drafts/current/.
Internet-Drafts are draft documents valid for a maximum of six months
and may be updated, replaced, or obsoleted by other documents at any
time. It is inappropriate to use Internet-Drafts as reference
material or to cite them other than as "work in progress."
This Internet-Draft will expire on September 10, 2020.
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Copyright Notice
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This document is subject to BCP 78 and the IETF Trust's Legal
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Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 3
1.1. Terminology . . . . . . . . . . . . . . . . . . . . . . . 3
2. Technical Prescription . . . . . . . . . . . . . . . . . . . 3
3. Technical Identification . . . . . . . . . . . . . . . . . . 4
3.1. Points of Control . . . . . . . . . . . . . . . . . . . . 4
3.2. Application Layer . . . . . . . . . . . . . . . . . . . . 6
3.2.1. HTTP Request Header Identification . . . . . . . . . 6
3.2.2. HTTP Response Header Identification . . . . . . . . . 7
3.2.3. Instrumenting Content Distributors . . . . . . . . . 7
3.2.4. Deep Packet Inspection (DPI) Identification . . . . . 9
3.3. Transport Layer . . . . . . . . . . . . . . . . . . . . . 11
3.3.1. Shallow Packet Inspection and TCP/IP Header
Identification . . . . . . . . . . . . . . . . . . . 11
3.3.2. Protocol Identification . . . . . . . . . . . . . . . 12
4. Technical Interference . . . . . . . . . . . . . . . . . . . 13
4.1. Application Layer . . . . . . . . . . . . . . . . . . . . 13
4.1.1. DNS Interference . . . . . . . . . . . . . . . . . . 13
4.2. Transport Layer . . . . . . . . . . . . . . . . . . . . . 15
4.2.1. Performance Degradation . . . . . . . . . . . . . . . 15
4.2.2. Packet Dropping . . . . . . . . . . . . . . . . . . . 16
4.2.3. RST Packet Injection . . . . . . . . . . . . . . . . 17
4.3. Multi-layer and Non-layer . . . . . . . . . . . . . . . . 18
4.3.1. Distributed Denial of Service (DDoS) . . . . . . . . 18
4.3.2. Network Disconnection or Adversarial Route
Announcement . . . . . . . . . . . . . . . . . . . . 19
5. Non-Technical Prescription . . . . . . . . . . . . . . . . . 19
6. Non-Technical Interference . . . . . . . . . . . . . . . . . 20
6.1. Self-Censorship . . . . . . . . . . . . . . . . . . . . . 20
6.2. Server Takedown . . . . . . . . . . . . . . . . . . . . . 20
6.3. Notice and Takedown . . . . . . . . . . . . . . . . . . . 20
7. Contributors . . . . . . . . . . . . . . . . . . . . . . . . 21
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8. Informative References . . . . . . . . . . . . . . . . . . . 21
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 33
1. Introduction
Censorship is where an entity in a position of power - such as a
government, organization, or individual - suppresses communication
that it considers objectionable, harmful, sensitive, politically
incorrect or inconvenient [WP-Def-2020]. (Although censors that
engage in censorship must do so through legal, military, or other
means, this document focuses largely on technical mechanisms used to
achieve network censorship.)
This document describes the technical mechanisms that censorship
regimes around the world use to block or degrade Internet traffic
(see [RFC7754] for a discussion of Internet blocking and filtering in
terms of implications for Internet architecture, rather than end-user
access to content and services).
1.1. Terminology
We describe three elements of Internet censorship - prescription,
identification, and interference - and structure the document in
three major sections corresponding to each. Prescription is the
process by which censors determine what types of material they should
block, i.e. they decide to block a list of pornographic websites.
Identification is the process by which censors classify specific
traffic to be blocked or impaired, i.e. the censor blocks or impairs
all webpages containing "sex" in the title or traffic to
www.sex.example. Interference is the process by which the censor
intercedes in communication and prevents access to censored materials
by blocking access or impairing the connection.
2. Technical Prescription
Prescription is the process of figuring out what censors would like
to block [Glanville-2008]. Generally, censors aggregate information
"to block" in blocklists or using real-time heuristic assessment of
content [Ding-1999]. Some national networks are designed to more
naturally to serve as points of control [Leyba-2019] and there are
indications that online censors are starting to use probabilistic
machine learning techniques as well [Tang-2016].
There are typically three types of blocklists: Keyword, domain name,
or Internet Protocol (IP) address. Keyword and domain name blocking
take place at the application level (e.g. HTTP), whereas IP blocking
tends to take place using IP addresses in IPv4/IPv6 headers. The
mechanisms for building up these blocklists are varied. Censors can
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purchase from private industry "content control" software, such as
SmartFilter, which allows filtering from broad categories that they
would like to block, such as gambling or pornography. In these
cases, these private services attempt to categorize every semi-
questionable website as to allow for meta-tag blocking (similarly,
they tune real-time content heuristic systems to map their
assessments onto categories of objectionable content).
Countries that are more interested in retaining specific political
control, a desire which requires swift and decisive action, often
have ministries or organizations, such as the Ministry of Industry
and Information Technology in China, the Ministry of Culture and
Islamic Guidance in Iran, specific to copyright in France
[HADOPI-2020] and across the EU for consumer protection law
[Reda-2017], all of which maintain their own blocklists.
3. Technical Identification
3.1. Points of Control
Internet censorship, necessarily, takes place over a network.
Network design gives censors a number of different points-of-control
where they can identify the content they are interested in filtering.
An important aspect of pervasive technical interception is the
necessity to rely on software or hardware to intercept the content
the censor is interested in. This requirement, the need to have the
interception mechanism located somewhere, logically or physically,
implicates various general points-of-control:
o Internet Backbone: If a censor controls the gateways into a
region, they can filter undesirable traffic that is traveling into
and out of the region by packet sniffing and port mirroring at the
relevant exchange points. Censorship at this point of control is
most effective at controlling the flow of information between a
region and the rest of the Internet, but is ineffective at
identifying content traveling between the users within a region.
Some national network designs naturally serve as more effective
chokepoints and points of control [Leyba-2019].
o Internet Service Providers: Internet Service Providers have until
now been the most frequently exploited point of control. They
have the benefit of being easily enumerable by a censor - often
falling under the jurisdictional or operational control of a
censor in an indisputable way - with the additional feature that
an ISP has the ability to identify the regional and international
traffic of all their users. The censor's filtration mechanisms
can be placed on an ISP via governmental mandates, ownership, or
voluntary/coercive influence.
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o Institutions: Private institutions such as corporations, schools,
and Internet cafes can put filtration mechanisms in place. These
mechanisms are occasionally at the request of a government censor,
but can also be implemented to help achieve institutional goals,
such as fostering a particular moral outlook on life by school-
children, independent of broader society or government goals.
o Personal Devices: Censors can mandate censorship software be
installed on the device level. This has many disadvantages in
terms of scalability, ease-of-circumvention, and operating system
requirements. (Of course, if a personal device is treated with
censorship software before sale and this software is difficult to
reconfigure, this may work in favor of those seeking to control
information, say for children, students, customers, or employees.)
The emergence of mobile devices exacerbate these feasibility
problems. This software can also be mandated by institutional
actors acting on non-governmentally mandated moral imperatives.
o Services: Application service providers can be pressured, coerced,
or legally required to censor specific content or flows of data.
Service providers naturally face incentives to maximize their
potential customer base and potential service shutdowns or legal
liability due to censorship efforts may seem much less attractive
than potentially excluding content, users, or uses of their
service. Services have increasingly become focal points of
censorship discussions, as well as the focus of discussions of
moral imperatives to use censorship tools.
o Certificate Authorities for Public-Key Infrastructures (PKIs):
Authorities that issue cryptographically secured resources can be
a significant point of control. Certificate Authorities that
issue certificates to domain holders for TLS/HTTPS (the Web PKI)
or Regional/Local Internet Registries (RIRs) that issue Route
Origination Authorizations (ROAs) to BGP operators can be forced
to issue rogue certificates that may allow compromises in
confidentiality guarantees - allowing censorship software to
engage in identification and interference where not possible
before - or integrity guarantees - allowing, for example,
adversarial routing of traffic.
o Content Distribution Networks (CDNs): CDNs seek to collapse
network topology in order to better locate content closer to the
service's users in order to reduce the latency of content
transmissions and thereby improve quality of service. The CDN
service's content servers, located "close" to the user in a
network-sense, can be powerful points of control for censors,
especially if the location of CDN content repositories allow for
easier interference.
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At all levels of the network hierarchy, the filtration mechanisms
used to detect undesirable traffic are essentially the same: a censor
either directly sniffs transmitting packets and identifies
undesirable content, and then uses a blocking or shaping mechanism to
prevent or impair access, or requests that an actor ancillary to the
censor, such as a private entity, performs these functions.
Identification of undesirable traffic can occur at the application,
transport, or network layer of the IP stack. Censors often focus on
web traffic, so the relevant protocols tend to be filtered in
predictable ways (see Section 3.2.1 and Section 3.2.2). For example,
a subversive image would always make it past a keyword filter, but
the IP address of the site serving the image may be blocklisted when
identified as a provider of undesirable content.
3.2. Application Layer
3.2.1. HTTP Request Header Identification
An HTTP header contains a lot of useful information for traffic
identification; although "host" is the only required field in an HTTP
request header (for HTTP/1.1 and later), an HTTP method field is
necessary to do anything useful. As such, "method" and "host" are
the two fields used most often for ubiquitous censorship. A censor
can sniff traffic and identify a specific domain name (host) and
usually a page name (GET /page) as well. This identification
technique is usually paired with TCP/IP header identification (see
Section 3.3.1) for a more robust method.
Tradeoffs: Request Identification is a technically straight-forward
identification method that can be easily implemented at the Backbone
or ISP level. The hardware needed for this sort of identification is
cheap and easy-to-acquire, making it desirable when budget and scope
are a concern. HTTPS will encrypt the relevant request and response
fields, so pairing with TCP/IP identification (see Section 3.3.1) is
necessary for filtering of HTTPS. However, some countermeasures such
as URL obfuscation can trivially defeat simple forms of HTTP Request
Header Identification (for example, two cooperating endpoints - an
instrumented web server and client - could use a simple character
rotation technique to obfuscate the "host" in an HTTP request. E.g.,
a given letter in a URL can be replaced by one 13 characters ahead of
it in the alphabet, such that a URL http://example.com becomes
uggc://rknzcyr.pbz, potentially thwarting techniques that match
against "host" header values.).
Empirical Examples: Studies exploring censorship mechanisms have
found evidence of HTTP header/ URL filtering in many countries,
including Bangladesh, Bahrain, China, India, Iran, Malaysia,
Pakistan, Russia, Saudi Arabia, South Korea, Thailand, and Turkey
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[Verkamp-2012] [Nabi-2013] [Aryan-2012]. Commercial technologies
such as the McAfee SmartFilter and NetSweeper are often purchased by
censors [Dalek-2013]. These commercial technologies use a
combination of HTTP Request Identification and TCP/IP Header
Identification to filter specific URLs. Dalek et al. and Jones et
al. identified the use of these products in the wild [Dalek-2013]
[Jones-2014].
3.2.2. HTTP Response Header Identification
While HTTP Request Header Identification relies on the information
contained in the HTTP request from client to server, response
identification uses information sent in response by the server to
client to identify undesirable content.
Tradeoffs: As with HTTP Request Header Identification, the techniques
used to identify HTTP traffic are well-known, cheap, and relatively
easy to implement, but is made useless by HTTPS, because the response
in HTTPS is encrypted, including headers.
The response fields are also less helpful for identifying content
than request fields, as "Server" could easily be identified using
HTTP Request Header identification, and "Via" is rarely relevant.
HTTP Response censorship mechanisms normally let the first n packets
through while the mirrored traffic is being processed; this may allow
some content through and the user may be able to detect that the
censor is actively interfering with undesirable content.
Empirical Examples: In 2009, Jong Park et al. at the University of
New Mexico demonstrated that the Great Firewall of China (GFW) has
used this technique [Crandall-2010]. However, Jong Park et al. found
that the GFW discontinued this practice during the course of the
study. Due to the overlap in HTTP response filtering and keyword
filtering (see Section 3.2.3), it is likely that most censors rely on
keyword filtering over TCP streams instead of HTTP response
filtering.
3.2.3. Instrumenting Content Distributors
Many governments pressure content providers to censor themselves, or
provide the legal framework within which content distributors are
incentivised to follow the content restriction preferences of agents
external to the content distributor [Boyle-1997]. Due to the
extensive reach of such censorship, we need to define content
distributor as any service that provides utility to users, including
everything from web sites to locally installed programs. A commonly
used method of instrumenting content distributors consists of keyword
identification to detect restricted terms on their platform. The
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terms on such keyword lists may be provided by the government or the
content provider may be expected to come up with their own list. A
different method of instrumenting content distributors consists of
requiring a distributor to disassociate with some categories of
users. (See also Section 6.3.)
Tradeoffs: By instrumenting content distributors to identify
restricted content or content providers, the censor can gain new
information at the cost of political capital with the companies it
forces or encourages to participate in censorship. For example, the
censor can gain insight about the content of encrypted traffic by
coercing web sites to identify restricted content. Coercing content
distributors to regulate users, categories of users, content and
content providers may encourage users and content providers to
exhibit self-censorship, an additional advantage for censors (see
Section 6.1). The tradeoffs for instrumenting content distributors
are highly dependent on the content provider and the requested
assistance. The typical concern is that the targeted keywords or
categories of users are too broad, risk being too broadly applied or
are not subjected to a sufficiently robust legal process prior to
their mandatory application (see p. 8 of [EC-2012]).
Empirical Examples: Researchers have discovered keyword
identification by content providers on platforms ranging from instant
messaging applications [Senft-2013] to search engines [Rushe-2015]
[Cheng-2010] [Whittaker-2013] [BBC-2013] [Condliffe-2013]. To
demonstrate the prevalence of this type of keyword identification, we
look to search engine censorship.
Search engine censorship demonstrates keyword identification by
content providers and can be regional or worldwide. Implementation
is occasionally voluntary, but normally it is based on laws and
regulations of the country a search engine is operating in. The
keyword blocklists are most likely maintained by the search engine
provider. China is known to require search engine providers to
"voluntarily" maintain search term blocklists to acquire/keep an
Internet content provider (ICP) license [Cheng-2010]. It is clear
these blocklists are maintained by each search engine provider based
on the slight variations in the intercepted searches [Zhu-2011]
[Whittaker-2013]. The United Kingdom has been pushing search engines
to self-censor with the threat of litigation if they don't do it
themselves: Google and Microsoft have agreed to block more than
100,000 queries in U.K. to help combat abuse [BBC-2013]
[Condliffe-2013]. European Union law, as well as US law, requires
modification of search engine results in response to either
copyright, trademark, data protection or defamation concerns
[EC-2012].
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Depending on the output, search engine keyword identification may be
difficult or easy to detect. In some cases specialized or blank
results provide a trivial enumeration mechanism, but more subtle
censorship can be difficult to detect. In February 2015, Microsoft's
search engine, Bing, was accused of censoring Chinese content outside
of China [Rushe-2015] because Bing returned different results for
censored terms in Chinese and English. However, it is possible that
censorship of the largest base of Chinese search users, China, biased
Bing's results so that the more popular results in China (the
uncensored results) were also more popular for Chinese speakers
outside of China.
Disassociation by content distributors from certain categories of
users has happened for instance in Spain, as a result of the conflict
between the Catalunyan independence movement and the Spanish legal
presumption of a unitary state [Lomas-2019]. E-sport event
organizers have also disassociated themselves from top players who
expressed political opinions in relation to the 2019 Hong Kong
protests [Victor-2019]. See also Section 4.3.2.
3.2.4. Deep Packet Inspection (DPI) Identification
Deep Packet Inspection has become computationally feasible as a
censorship mechanism in recent years [Wagner-2009]. Unlike other
techniques, DPI reassembles network flows to examine the application
"data" section, as opposed to only the header, and is therefore often
used for keyword identification. DPI also differs from other
identification technologies because it can leverage additional packet
and flow characteristics, i.e. packet sizes and timings, to identify
content. To prevent substantial quality of service (QoS) impacts,
DPI normally analyzes a copy of data while the original packets
continue to be routed. Typically, the traffic is split using either
a mirror switch or fiber splitter, and analyzed on a cluster of
machines running Intrusion Detection Systems (IDS) configured for
censorship.
Tradeoffs: DPI is one of the most expensive identification mechanisms
and can have a large QoS impact [Porter-2010]. When used as a
keyword filter for TCP flows, DPI systems can cause also major
overblocking problems. Like other techniques, DPI is less useful
against encrypted data, though DPI can leverage unencrypted elements
of an encrypted data flow (e.g., the Server Name Indicator (SNI) sent
in the clear for TLS) or statistical information about an encrypted
flow (e.g., video takes more bandwidth than audio or textual forms of
communication) to identify traffic.
Other kinds of information can be inferred by comparing certain
unencrypted elements exchanged during TLS handshakes to similar data
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points from known sources. This practice, called TLS fingerprinting,
allows a probabilistic identification of a party's operating system,
browser, or application based on a comparison of the specific
combinations of TLS version, ciphersuites, compression options, etc.
sent in the ClientHello message to similar signatures found in
unencrypted traffic [Husak-2016].
Despite these problems, DPI is the most powerful identification
method and is widely used in practice. The Great Firewall of China
(GFW), the largest censorship system in the world, has used DPI to
identify restricted content over HTTP and DNS and inject TCP RSTs and
bad DNS responses, respectively, into connections [Crandall-2010]
[Clayton-2006] [Anonymous-2014].
Empirical Examples: Several studies have found evidence of DPI being
used to censor content and tools. Clayton et al. Crandal et al.,
Anonymous, and Khattak et al., all explored the GFW and Khattak et
al. even probed the firewall to discover implementation details like
how much state it stores [Crandall-2010] [Clayton-2006]
[Anonymous-2014] [Khattak-2013]. The Tor project claims that China,
Iran, Ethiopia, and others must have used DPI to block the obfs2
protocol [Wilde-2012]. Malaysia has been accused of using targeted
DPI, paired with DDoS, to identify and subsequently knockout pro-
opposition material [Wagstaff-2013]. It also seems likely that
organizations not so worried about blocking content in real-time
could use DPI to sort and categorically search gathered traffic using
technologies such as NarusInsight [Hepting-2011].
3.2.4.1. Server Name Indication
In encrypted connections using Transport Layer Security (TLS), there
may be servers that host multiple "virtual servers" at a given
network address, and the client will need to specify in the
(unencrypted) Client Hello message which domain name it seeks to
connect to (so that the server can respond with the appropriate TLS
certificate) using the Server Name Indication (SNI) TLS extension
[RFC6066]. Since SNI is sent in the clear, censors and filtering
software can use it as a basis for blocking, filtering, or impairment
by dropping connections to domains that match prohibited content
(e.g., bad.foo.example may be censored while good.foo.example is not)
[Shbair-2015].
Domain fronting has been one popular way to avoid identification by
censors [Fifield-2015]. To avoid identification by censors,
applications using domain fronting put a different domain name in the
SNI extension than the one encrypted by HTTPS. The visible SNI would
indicate an unblocked domain, while the blocked domain remains hidden
in the encrypted application header. Some encrypted messaging
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services relied on domain fronting to enable their provision in
countries employing SNI-based filtering. These services used the
cover provided by domains for which blocking at the domain level
would be undesirable to hide their true domain names. However, the
companies holding the most popular domains have since reconfigured
their software to prevent this practice. It may be possible to
achieve similar results using potential future options to encrypt SNI
in TLS 1.3.
Tradeoffs: Some clients do not send the SNI extension (e.g., clients
that only support versions of SSL and not TLS) or will fall back to
SSL if a TLS connection fails, rendering this method ineffective. In
addition, this technique requires deep packet inspection techniques
that can be computationally and infrastructurally expensive and
improper configuration of an SNI-based block can result in
significant overblocking, e.g., when a second-level domain like
populardomain.example is inadvertently blocked. In the case of
encrypted SNI, pressure to censor may transfer to other points of
intervention, such as content and application providers.
Empirical Examples: There are many examples of security firms that
offer SNI-based filtering products [Trustwave-2015] [Sophos-2015]
[Shbair-2015], and the governments of China, Egypt, Iran, Qatar,
South Korea, Turkey, Turkmenistan, and the UAE all do widespread SNI
filtering or blocking [OONI-2018] [OONI-2019] [NA-SK-2019]
[CitizenLab-2018] [Gatlan-2019] [Chai-2019] [Grover-2019]
[Singh-2019].
3.3. Transport Layer
3.3.1. Shallow Packet Inspection and TCP/IP Header Identification
Of the various shallow packet inspection methods, TCP/IP Header
Identification is the most pervasive, reliable, and predictable type
of identification. TCP/IP headers contain a few invaluable pieces of
information that must be transparent for traffic to be successfully
routed: destination and source IP address and port. Destination and
Source IP are doubly useful, as not only does it allow a censor to
block undesirable content via IP blocklisting, but also allows a
censor to identify the IP of the user making the request. Port is
useful for allowlisting certain applications.
Trade-offs: TCP/IP identification is popular due to its simplicity,
availability, and robustness.
TCP/IP identification is trivial to implement, but is difficult to
implement in backbone or ISP routers at scale, and is therefore
typically implemented with DPI. Blocklisting an IP is equivalent to
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installing a /32 route on a router and due to limited flow table
space, this cannot scale beyond a few thousand IPs at most. IP
blocking is also relatively crude, leading to overblocking, and
cannot deal with some services like Content Distribution Networks
(CDN), that host content at hundreds or thousands of IP addresses.
Despite these limitations, IP blocking is extremely effective because
the user needs to proxy their traffic through another destination to
circumvent this type of identification.
Port-blocking is generally not useful because many types of content
share the same port and it is possible for censored applications to
change their port. For example, most HTTP traffic goes over port 80,
so the censor cannot differentiate between restricted and allowed
content solely on the basis of port. Port allowlisting is
occasionally used, where a censor limits communication to approved
ports, such as 80 for HTTP traffic and is most effective when used in
conjunction with other identification mechanisms. For example, a
censor could block the default HTTPS port, port 443, thereby forcing
most users to fall back to HTTP. An important counter-example is
that port 25 (SMTP) has long been blocked on residential ISPs'
networks, ostensibly to reduce the potential for email spam, but also
prohibiting residential ISP customers to run their own email servers.
3.3.2. Protocol Identification
Censors sometimes identify entire protocols to be blocked using a
variety of traffic characteristics. For example, Iran impairs the
performance of HTTPS traffic, a protocol that prevents further
analysis, to encourage users to switch to HTTP, a protocol that they
can analyze [Aryan-2012]. A simple protocol identification would be
to recognize all TCP traffic over port 443 as HTTPS, but more
sophisticated analysis of the statistical properties of payload data
and flow behavior, would be more effective, even when port 443 is not
used [Hjelmvik-2010] [Sandvine-2014].
If censors can detect circumvention tools, they can block them, so
censors like China are extremely interested in identifying the
protocols for censorship circumvention tools. In recent years, this
has devolved into an arms race between censors and circumvention tool
developers. As part of this arms race, China developed an extremely
effective protocol identification technique that researchers call
active probing or active scanning.
In active probing, the censor determines whether hosts are running a
circumvention protocol by trying to initiate communication using the
circumvention protocol. If the host and the censor successfully
negotiate a connection, then the censor conclusively knows that host
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is running a circumvention tool. China has used active scanning to
great effect to block Tor [Winter-2012].
Trade-offs: Protocol identification necessarily only provides insight
into the way information is traveling, and not the information
itself.
Protocol identification is useful for detecting and blocking
circumvention tools, like Tor, or traffic that is difficult to
analyze, like VoIP or SSL, because the censor can assume that this
traffic should be blocked. However, this can lead to over-blocking
problems when used with popular protocols. These methods are
expensive, both computationally and financially, due to the use of
statistical analysis, and can be ineffective due to their imprecise
nature.
Empirical Examples: Protocol identification can be easy to detect if
it is conducted in real time and only a particular protocol is
blocked, but some types of protocol identification, like active
scanning, are much more difficult to detect. Protocol identification
has been used by Iran to identify and throttle SSH traffic to make it
unusable [Anonymous-2007] and by China to identify and block Tor
relays [Winter-2012]. Protocol identification has also been used for
traffic management, such as the 2007 case where Comcast in the United
States used RST injection to interrupt BitTorrent Traffic
[Winter-2012].
4. Technical Interference
4.1. Application Layer
4.1.1. DNS Interference
There are a variety of mechanisms that censors can use to block or
filter access to content by altering responses from the DNS
[AFNIC-2013] [ICANN-SSAC-2012], including blocking the response,
replying with an error message, or responding with an incorrect
address.
"DNS mangling" is a network-level technique where an incorrect IP
address is returned in response to a DNS query to a censored
destination. An example of this is what some Chinese networks do (we
are not aware of any other wide-scale uses of mangling). On those
Chinese networks, every DNS request in transit is examined
(presumably by network inspection technologies such as DPI) and, if
it matches a censored domain, a false response is injected. End
users can see this technique in action by simply sending DNS requests
to any unused IP address in China (see example below). If it is not
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a censored name, there will be no response. If it is censored, a
forged response will be returned. For example, using the command-
line dig utility to query an unused IP address in China of 192.0.2.2
for the name "www.uncensored.example" compared with
"www.censored.example" (censored at the time of writing), we get a
forged IP address "198.51.100.0" as a response:
% dig +short +nodnssec @192.0.2.2 A www.uncensored.example
;; connection timed out; no servers could be reached
% dig +short +nodnssec @192.0.2.2 A www.censored.example
198.51.100.0
There are also cases of what is colloquially called "DNS lying",
where a censor mandates that the DNS responses provided - by an
operator of a recursive resolver such as an Internet access provider
- be different than what authoritative resolvers would provide
[Bortzmayer-2015].
DNS cache poisoning refers to a mechanism where a censor interferes
with the response sent by an authoritative DNS resolver to a
recursive resolver by responding more quickly than the authoritative
resolver can respond with an alternative IP address [Halley-2008].
Cache poisoning occurs after the requested site's name servers
resolve the request and attempt to forward the true IP back to the
requesting device; on the return route the resolved IP is recursively
cached by each DNS server that initially forwarded the request.
During this caching process if an undesirable keyword is recognized,
the resolved IP is "poisoned" and an alternative IP (or NXDOMAIN
error) is returned more quickly than the upstream resolver can
respond, causing a forged IP address to be cached (and potentially
recursively so). The alternative IPs usually direct to a nonsense
domain or a warning page. Alternatively, Iranian censorship appears
to prevent the communication en-route, preventing a response from
ever being sent [Aryan-2012].
Trade-offs: These forms of DNS interference require the censor to
force a user to traverse a controlled DNS hierarchy (or intervening
network on which the censor serves as a Active Pervasive Attacker
[RFC7624] to rewrite DNS responses) for the mechanism to be
effective. It can be circumvented by using alternative DNS resolvers
(such as any of the public DNS resolvers) that may fall outside of
the jurisdictional control of the censor, or Virtual Private Network
(VPN) technology. DNS mangling and cache poisoning also imply
returning an incorrect IP to those attempting to resolve a domain
name, but in some cases the destination may be technically
accessible; over HTTP, for example, the user may have another method
of obtaining the IP address of the desired site and may be able to
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access it if the site is configured to be the default server
listening at this IP address. Target blocking has also been a
problem, as occasionally users outside of the censors region will be
directed through DNS servers or DNS-rewriting network equipment
controlled by a censor, causing the request to fail. The ease of
circumvention paired with the large risk of content blocking and
target blocking make DNS interference a partial, difficult, and less
than ideal censorship mechanism. Additionally, the above mechanisms
rely on DNSSEC not being deployed or DNSSEC validation not being
active on the client or recursive resolver.
Empirical Examples: DNS interference, when properly implemented, is
easy to identify based on the shortcomings identified above. Turkey
relied on DNS interference for its country-wide block of websites
such Twitter and YouTube for almost week in March of 2014 but the
ease of circumvention resulted in an increase in the popularity of
Twitter until Turkish ISPs implementing an IP blocklist to achieve
the governmental mandate [Zmijewski-2014]. Ultimately, Turkish ISPs
started hijacking all requests to Google and Level 3's international
DNS resolvers [Zmijewski-2014]. DNS interference, when incorrectly
implemented, has resulted in some of the largest "censorship
disasters". In January 2014, China started directing all requests
passing through the Great Fire Wall to a single domain,
dongtaiwang.com, due to an improperly configured DNS poisoning
attempt; this incident is thought to be the largest Internet-service
outage in history [AFP-2014] [Anon-SIGCOMM12]. Countries such as
China, Iran, Turkey, and the United States have discussed blocking
entire TLDs as well, but only Iran has acted by blocking all Israeli
(.il) domains [Albert-2011]. DNS-blocking is commonly deployed in
European countries to deal with undesirable content, such as child
abuse content (Norway, United Kingdom, Belgium, Denmark, Finland,
France, Germany, Ireland, Italy, Malta, the Netherlands, Poland,
Spain and Sweden [Wright-2013] [Eneman-2010]), online gambling
(Belgium, Bulgaria, Czech Republic, Cyprus, Denmark, Estonia, France,
Greece, Hungary, Italy, Latvia, Lithuania, Poland, Portugal, Romania,
Slovakia, Slovenia, Spain (see Section 6.3.2 of: [EC-gambling-2012],
[EC-gambling-2019])), copyright infringement (all European Economic
Area countries), hate-speech and extremism (France [Hertel-2015]) and
terrorism content (France [Hertel-2015]). Many European DNS
filtering systems function as described in section 6.2.
4.2. Transport Layer
4.2.1. Performance Degradation
While other interference techniques outlined in this section mostly
focus on blocking or preventing access to content, it can be an
effective censorship strategy in some cases to not entirely block
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access to a given destination, or service but instead degrade the
performance of the relevant network connection. The resulting user
experience for a site or service under performance degradation can be
so bad that users opt to use a different site, service, or method of
communication, or may not engage in communication at all if there are
no alternatives. Traffic shaping techniques that rate-limit the
bandwidth available to certain types of traffic is one example of a
performance degradation.
Trade offs: While implementing a performance degradation will not
always eliminate the ability of people to access a desire resource,
it may force them to use other means of communication where
censorship (or surveillance) is more easily accomplished.
Empirical Examples: Iran has been known to shape the bandwidth
available to HTTPS traffic to encourage unencrypted HTTP traffic
[Aryan-2012].
4.2.2. Packet Dropping
Packet dropping is a simple mechanism to prevent undesirable traffic.
The censor identifies undesirable traffic and chooses to not properly
forward any packets it sees associated with the traversing
undesirable traffic instead of following a normal routing protocol.
This can be paired with any of the previously described mechanisms so
long as the censor knows the user must route traffic through a
controlled router.
Trade offs: Packet Dropping is most successful when every traversing
packet has transparent information linked to undesirable content,
such as a Destination IP. One downside Packet Dropping suffers from
is the necessity of blocking all content from otherwise allowable IPs
based on a single subversive sub-domain; blogging services and github
repositories are good examples. China famously dropped all github
packets for three days based on a single repository hosting
undesirable content [Anonymous-2013]. The need to inspect every
traversing packet in close to real time also makes Packet Dropping
somewhat challenging from a QoS perspective.
Empirical Examples: Packet Dropping is a very common form of
technical interference and lends itself to accurate detection given
the unique nature of the time-out requests it leaves in its wake.
The Great Firewall of China has been observed using packet dropping
as one of its primary mechanisms of technical censorship
[Ensafi-2013]. Iran has also used Packet Dropping as the mechanisms
for throttling SSH [Aryan-2012]. These are but two examples of a
ubiquitous censorship practice.
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4.2.3. RST Packet Injection
Packet injection, generally, refers to a man-in-the-middle (MITM)
network interference technique that spoofs packets in an established
traffic stream. RST packets are normally used to let one side of TCP
connection know the other side has stopped sending information, and
thus the receiver should close the connection. RST Packet Injection
is a specific type of packet injection attack that is used to
interrupt an established stream by sending RST packets to both sides
of a TCP connection; as each receiver thinks the other has dropped
the connection, the session is terminated.
Trade-offs: Although ineffective against non-TCP protocols (QUIC,
IPSec), RST Packet Injection has a few advantages that make it
extremely popular as a censorship technique. RST Packet Injection is
an out-of-band interference mechanism, allowing the avoidance of the
the QoS bottleneck one can encounter with inline techniques such as
Packet Dropping. This out-of-band property allows a censor to
inspect a copy of the information, usually mirrored by an optical
splitter, making it an ideal pairing for DPI and protocol
identification [Weaver-2009] (this asynchronous version of a MITM is
often called a Man-on-the-Side (MOTS)). RST Packet Injection also
has the advantage of only requiring one of the two endpoints to
accept the spoofed packet for the connection to be interrupted.
The difficult part of RST Packet Injection is spoofing "enough"
correct information to ensure one end-point accepts a RST packet as
legitimate; this generally implies a correct IP, port, and (TCP)
sequence number. Sequence number is the hardest to get correct, as
[RFC0793] specifies an RST Packet should be in-sequence to be
accepted, although the RFC also recommends allowing in-window packets
as "good enough". This in-window recommendation is important, as if
it is implemented it allows for successful Blind RST Injection
attacks [Netsec-2011]. When in-window sequencing is allowed, It is
trivial to conduct a Blind RST Injection, a blind injection implies
the censor doesn't know any sensitive (encrypted) sequencing
information about the TCP stream they are injecting into, they can
simply enumerate the ~70000 possible windows; this is particularly
useful for interrupting encrypted/obfuscated protocols such as SSH or
Tor. RST Packet Injection relies on a stateful network, making it
useless against UDP connections. RST Packet Injection is among the
most popular censorship techniques used today given its versatile
nature and effectiveness against all types of TCP traffic.
Empirical Examples: RST Packet Injection, as mentioned above, is most
often paired with identification techniques that require splitting,
such as DPI or protocol identification. In 2007, Comcast was accused
of using RST Packet Injection to interrupt traffic it identified as
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BitTorrent [Schoen-2007], this later led to a US Federal
Communications Commission ruling against Comcast [VonLohmann-2008].
China has also been known to use RST Packet Injection for censorship
purposes. This interference is especially evident in the
interruption of encrypted/obfuscated protocols, such as those used by
Tor [Winter-2012].
4.3. Multi-layer and Non-layer
4.3.1. Distributed Denial of Service (DDoS)
Distributed Denial of Service attacks are a common attack mechanism
used by "hacktivists" and malicious hackers, but censors have used
DDoS in the past for a variety of reasons. There is a huge variety
of DDoS attacks [Wikip-DoS], but on a high level two possible impacts
tend to occur; a flood attack results in the service being unusable
while resources are being spent to flood the service, a crash attack
aims to crash the service so resources can be reallocated elsewhere
without "releasing" the service.
Trade-offs: DDoS is an appealing mechanism when a censor would like
to prevent all access to undesirable content, instead of only access
in their region for a limited period of time, but this is really the
only uniquely beneficial feature for DDoS as a censorship technique.
The resources required to carry out a successful DDoS against major
targets are computationally expensive, usually requiring renting or
owning a malicious distributed platform such as a botnet, and
imprecise. DDoS is an incredibly crude censorship technique, and
appears to largely be used as a timely, easy-to-access mechanism for
blocking undesirable content for a limited period of time.
Empirical Examples: In 2012 the U.K.'s GCHQ used DDoS to temporarily
shutdown IRC chat rooms frequented by members of Anonymous using the
Syn Flood DDoS method; Syn Flood exploits the handshake used by TCP
to overload the victim server with so many requests that legitimate
traffic becomes slow or impossible [Schone-2014] [CERT-2000].
Dissenting opinion websites are frequently victims of DDoS around
politically sensitive events in Burma [Villeneuve-2011]. Controlling
parties in Russia [Kravtsova-2012], Zimbabwe [Orion-2013], and
Malaysia [Muncaster-2013] have been accused of using DDoS to
interrupt opposition support and access during elections. In 2015,
China launched a DDoS attack using a true MITM system collocated with
the Great Firewall, dubbed "Great Cannon", that was able to inject
JavaScript code into web visits to a Chinese search engine that
commandeered those user agents to send DDoS traffic to various sites
[Marczak-2015].
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4.3.2. Network Disconnection or Adversarial Route Announcement
While it is perhaps the crudest of all censorship techniques, there
is no more effective way of making sure undesirable information isn't
allowed to propagate on the web than by shutting off the network.
The network can be logically cut off in a region when a censoring
body withdraws all of the Boarder Gateway Protocol (BGP) prefixes
routing through the censor's country.
Trade-offs: The impact to a network disconnection in a region is huge
and absolute; the censor pays for absolute control over digital
information with all the benefits the Internet brings; this is never
a long-term solution for any rational censor and is normally only
used as a last resort in times of substantial unrest.
Empirical Examples: Network Disconnections tend to only happen in
times of substantial unrest, largely due to the huge social,
political, and economic impact such a move has. One of the first,
highly covered occurrences was with the Junta in Myanmar employing
Network Disconnection to help Junta forces quash a rebellion in 2007
[Dobie-2007]. China disconnected the network in the Xinjiang region
during unrest in 2009 in an effort to prevent the protests from
spreading to other regions [Heacock-2009]. The Arab Spring saw the
the most frequent usage of Network Disconnection, with events in
Egypt and Libya in 2011 [Cowie-2011] [Cowie-2011b], and Syria in 2012
[Thomson-2012]. Russia has indicated that it will attempt to
disconnect all Russian networks from the global internet in April
2019 as part of a test of the nation's network independence. Reports
also indicate that, as part of the test disconnect, Russian telecom
firms must now route all traffic to state-operated monitoring points
[Cimpanu-2019]. India was the country that saw the largest number of
internet shutdowns per year in 2016 and 2017 [Dada-2017].
5. Non-Technical Prescription
As the name implies, sometimes manpower is the easiest way to figure
out which content to block. Manual Filtering differs from the common
tactic of building up blocklists in that it doesn't necessarily
target a specific IP or DNS, but instead removes or flags content.
Given the imprecise nature of automatic filtering, manually sorting
through content and flagging dissenting websites, blogs, articles and
other media for filtration can be an effective technique. This
filtration can occur on the Backbone/ISP level - China's army of
monitors is a good example [BBC-2013b] - but more commonly manual
filtering occurs on an institutional level. Internet Content
Providers such as Google or Weibo, require a business license to
operate in China. One of the prerequisites for a business license is
an agreement to sign a "voluntary pledge" known as the "Public Pledge
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on Self-discipline for the Chinese Internet Industry". The failure
to "energetically uphold" the pledged values can lead to the ICPs
being held liable for the offending content by the Chinese government
[BBC-2013b].
6. Non-Technical Interference
6.1. Self-Censorship
Self-censorship is one of the most interesting and effective types of
censorship: a mix of Bentham's Panopticon [Bentham-1791], cultural
manipulation, intelligence gathering, and offline enforcement.
Simply put, self-censorship is when a censor creates an atmosphere
where users censor themselves. This can be achieved through
controlling information, intimidating would-be dissidents, swaying
public thought, and creating apathy. Self-censorship is difficult to
document, as when it is implemented effectively the only noticeable
evidence is a lack of undesirable content; instead one must look at
the tools and techniques used by censors to encourage self-
censorship. Controlling Information relies on traditional censorship
techniques, or by forcing all users to connect through an intranet,
such as in North Korea. Intimidation is often achieved through
allowing Internet users to post "whatever they want," but arresting
those who post about dissenting views, this technique is incredibly
common [Calamur-2013] [AP-2012] [Hopkins-2011] [Guardian-2014]
[Johnson-2010]. A good example of swaying public thought is China's
"50-Cent Party," reported to be composed of somewhere between 20,000
[Bristow-2013] and 300,000 [Fareed-2008] contributors who are paid to
"guide public thought" on local and regional issues as directed by
the Ministry of Culture. Creating apathy can be a side-effect of
successfully controlling information over time and is ideal for a
censorship regime [Gao-2014].
6.2. Server Takedown
Servers must have a physical location somewhere in the world. If
undesirable content is hosted in the censoring country the servers
can be physically seized or the hosting provider can be required to
prevent access [Anderson-2011].
6.3. Notice and Takedown
In many countries, legal mechanisms exist where an individual or
other content provider can issue a legal request to a content host
that requires the host to take down content. Examples include the
systems employed by companies like Google to comply with "Right to be
Forgotten" policies in the European Union [Google-RTBF], intermediary
liability rules for electronic platform providers [EC-2012], or the
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copyright-oriented notice and takedown regime of the United States
Digital Millennium Copyright Act (DMCA) Section 512 [DMLP-512].
7. Contributors
This document benefited from discussions with and input from David
Belson, Stephane Bortzmeyer, Vinicius Fortuna, Gurshabad Grover,
Andrew McConachie, Martin Nilsson, Michael Richardson, and Patrick
Vacek.
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channelling-demand-towards-1_en>.
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Ensafi, R., "Detecting Intentional Packet Drops on the
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Fifield, D., Lan, C., Hynes, R., Wegmann, P., and V.
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Gao, H., "Tiananmen, Forgotten", 2014,
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Gatlan, S., "South Korea is Censoring the Internet by
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Hertel, O., "Comment les autorites peuvent bloquer un site
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Husak, M., Cermak, M., Jirsik, T., and P. Celeda, "HTTPS
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Johnson, L., "Torture feared in arrest of Iraqi blogger",
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Kopel, K., "Operation Seizing Our Sites: How the Federal
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Leyba, K., Edwards, B., Freeman, C., Crandall, J., and S.
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Lomas, N., "Github removes Tsunami Democratic's APK after
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Muncaster, P., "Malaysian election sparks web blocking/
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Morgus, R., Sherman, J., and S. Nam, "Analysis: South
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Nabi, Z., "The Anatomy of Web Censorship in Pakistan",
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[RFC6066] Eastlake 3rd, D., "Transport Layer Security (TLS)
Extensions: Extension Definitions", RFC 6066,
DOI 10.17487/RFC6066, January 2011,
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[RFC7624] Barnes, R., Schneier, B., Jennings, C., Hardie, T.,
Trammell, B., Huitema, C., and D. Borkmann,
"Confidentiality in the Face of Pervasive Surveillance: A
Threat Model and Problem Statement", RFC 7624,
DOI 10.17487/RFC7624, August 2015,
<https://www.rfc-editor.org/info/rfc7624>.
[RFC7754] Barnes, R., Cooper, A., Kolkman, O., Thaler, D., and E.
Nordmark, "Technical Considerations for Internet Service
Blocking and Filtering", RFC 7754, DOI 10.17487/RFC7754,
March 2016, <https://www.rfc-editor.org/info/rfc7754>.
[RSF-2005]
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Schone, M., Esposito, R., Cole, M., and G. Greenwald,
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anonymous-hackers-n21361>.
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[Senft-2013]
Senft, A., "Asia Chats: Analyzing Information Controls and
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Shbair, W., Cholez, T., Goichot, A., and I. Chrisment,
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Tang, C., "In-depth analysis of the Great Firewall of
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Thomson, I., "Syria Cuts off Internet and Mobile
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[Victor-2019]
Victor, D., "Blizzard Sets Off Backlash for Penalizing
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Wagstaff, J., "In Malaysia, online election battles take a
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[Wilde-2012]
Wilde, T., "Knock Knock Knockin' on Bridges Doors", 2012,
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Authors' Addresses
Joseph Lorenzo Hall
Internet Society
Email: hall@isoc.org
Michael D. Aaron
CU Boulder
Email: michael.drew.aaron@gmail.com
Hall, et al. Expires September 10, 2020 [Page 33]
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Stan Adams
CDT
Email: sadams@cdt.org
Amelia Andersdotter
Email: amelia.ietf@andersdotter.cc
Ben Jones
Princeton
Email: bj6@cs.princeton.edu
Nick Feamster
U Chicago
Email: feamster@uchicago.edu
Hall, et al. Expires September 10, 2020 [Page 34]