NETWORK WORKING GROUP J. Hall
Internet-Draft M. Aaron
Intended status: Informational Center for Democracy and Technology
Expires: April 30, 2015 October 27, 2014
A Survey of Worldwide Censorship Techniques
draft-hall-censorship-tech-00
Abstract
This document describes the technical mechanisms used by censorship
regimes around the world to block or degrade 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.
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the Trust Legal Provisions and are provided without warranty as
described in the Simplified BSD License.
1. Introduction
2. Technical Aggregation
Aggregation is the process of figuring out what censors would like to
block. Generally, censors aggregate "to block" information in three
possible sorts of blacklists: Keyword, Domain Name, or IP. Keyword
and Domain Name blocking take place at the application level (e.g.
HTTP), whereas IP blocking tends to take place in the TCP/IP header.
The mechanisms for building up these blacklists are varied. Many
times private industries that sell "content control" software, such
as SmartFilter, provide their services to nations which can then pick
from broad categories, such as gambling or pornography, that they
would like to block [ref-1]. In these cases, the private services
embark on an attempt to label every semi-questionable website as to
allow for this metatag blocking. 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
or the Ministry of Culture and Islamic Guidance in Iran, which
maintain their own blacklists.
3. Technical Identification
3.1. Points of Control
Digital 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 four 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 sniffing and 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.
o Internet Service Providers: Internet Service Providers are perhaps
the most natural point-of-control. They have a benefit of being
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easily enumerable by a censor paired with 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.
o Institutions: Private institutions such as corporations, schools,
and cyber cafes can put filtration mechanisms in place. These
mechanisms are occasionally at the request of a censor, but are
more often implemented to help achieve institutional goals, such
as to prevent the viewing of pornography on school computers.
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. The emergence of mobile devices exacerbate these
feasibility problems.
At all levels of the network hierarchy, the filtration mechanisms
used to detect undesirable traffic are essentially the same: a censor
sniffs transmitting packets and identifies undesirable content, and
then uses a blocking or shaping mechanism to prevent or degrade
access. Identification of undesirable traffic can occur at the
application, transport, or network layer of the IP stack. Censors
are almost always concerned with web traffic, so the relevant
protocols tend to be filtered in predictable ways. 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 blacklisted when
identified as a provider of undesirable content.
3.2. Application Layer
3.2.1. HTTP Request Header Identification
A HTTP header contains a lot of useful information for traffic
identification; although host is the only required field in a HTTP
request header, a HTTP method field is necessary to do anything
useful. As such, the method and host fields are the two fields used
most often for ubiquitous censorship. As a censor, I 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 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 is necessary for
filtering of HTTPS. Empirical Examples: Empirical examples of pure
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HTTP Request Identification are unusually hard to identify due to the
lack of distinguishing charistics. Commercial technologies such as
the McAfee SmartFilter and NetSweeper are often purchased by censors
[ref-2]. These commercial technologies use a combination of HTTP
Request Identification and TCP/IP Header Identification to filter
specific URLs. There has not been research conducted to try and
identify if only one of these two techniques is being used.
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. Usually implemented at the
Backbone or ISP level, the technique normally relies on mirroring, or
duplicating the packets such that one can provide uninterrupted
service while inspecting the duplicates for undesirable content, to
prevent QoS degradation [ref-3] - the mirrored traffic is identified
by relevant response fields (such as Server or Via). 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 can let a page momentarily load before
blocking mechanisms kick in; giving the user a very clear indication
that the censor is actively interfering with undesirable content.
Empirical Examples: pointing to the "smoking-gun" examples in
response header identification is difficult for the same reasons
identifying requests is difficult. The best targeted evidence comes
from a 2010 study conducted by Jong Park at the University of New
Mexico. The study strongly indicates HTTP Response Header
Identification was being used as a censorship identification
technique in China from August 2008-January 2009 [ref-4].
3.2.3. Search Engine Keyword Identification
While technically similar to a HTTP request filter, the pervasiveness
of search engines blacklisting search terms warrants its own
attention. Search Engine Keyword Identification differentiates
itself from other keyword identification techniques by being
controlled by the company managing the search engine. Identification
can be regional or worldwide. Implementation is occasionally
voluntary, but normally is based on laws and regulations of the
country a search engine is operating in. The keyword blacklists are
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most likely maintained by the search engine provider. Tradeoffs:
Search Engine Keyword Identification is an inconvenience as opposed
to a hard block. As around half of all web traffic comes from search
[ref-5], disrupting the flow of users to undesirable content is an
effective method to redirect non-dedicated, curious users to less
subversive content. It is also likely an effective method at
encouraging self-censorship (see below) around the blocked content.
Empirical Examples: Search Engine Keyword Identification is one of
the easiest mechanisms to detect given the clear indicators, such as
a specialized or blank results, paired with a trivial enumeration
mechanism. China requires search engine providers to "voluntarily"
maintain search term blacklists to acquire/keep an ICP license
[ref-6]. It is clear these blacklists are maintained by each search
engine provider based on the slight variations in the intercepted
searches [ref-7][ref-8]. 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
100,00 queries in U.K. to help combat abuse [ref-9][ref-10].
3.2.4. Deep Packet Inspection (DPI) Identification
Deep Packet Inspection has become computationally feasible as a
censorship mechanism in the past 5 years [ref-11]. DPI differs from
other filtration techniques in that it examine the application "data"
section of traversing packets as opposed to only the header. To
prevent substantial QoS impacts, DPI normally works by splitting the
traffic, using either a mirror switch or fiber splitter, and
analyzing a copy of the traffic. Keyword identification is often
times used to flag undesirable content. Tradeoffs: While DPI can be
employed across entire networks, it is one of the most expensive
technical filtration mechanisms to implement and avoiding a large
impact to QoS is difficult [ref-12]. Often times a targeted approach
proves itself more feasible. Any encryption on the application
level, such as HTTPS, also makes DPI useless as a censorship
technique as the content typically analyzed is encrypted in this
case. DPI, when paired with a keyword filter, can cause major
overblocking problems if used indiscriminately. Empirical Evidence:
Identifying deep packet inspection censorship is non-trivial; one
must be sure that the undesirable content being filtered isn't being
caught by simpler mechanisms before claiming more advanced DPI
techniques are being used. The Tor project claims that China, Iran,
Ethiopia, and others must being using DPI to block the obsf2 protocol
[ref-13]. Malaysia has been accused of using target DPI, paired with
DDoS, to identify and subsequently knockout pro-opposition material
[ref-14]. 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 [ref-15].
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3.3. Transport Layer
3.3.1. TCP/IP Header Identification
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 cto block undesirable content via IP blacklisting, but
also allows a censor to identify the IP of the user making the
request. Port is useful for whitelisting certain applications or
forcing an HTTP proxy for non-technical users. Trade-offs: This
method of filtration is popular due to its simplicity, relative
cheapness, and wide availability. It is trivial to implement a
filtration mechanism at the Backbone, ISP, or Institutional level
that compares the IP address of a packet with a blacklist of IP
addresses. IP blocking is relatively crude, often leading to
overblocking, and one of the simplest to circumvent via VPN or proxy
as those either mask transport protocol within a tunnel or reroute
data that might have been blocked otherwise. Port blocking is semi-
effective at best. A censor can block communication on the default
port of an undesirable application (for example uTorrent defaults to
32459), but almost all applications allow the user to change ports.
Port whitelisting, where a censor only allow communication on
approved ports, such as 80 for HTTP traffic, is more often used.
This identification mechanism is often used in conjunction with HTTP
Identification. Empirical Examples: TCP/IP Header Identification is
pervasive. Some form of TCP/IP Header Identification is used by
most, if not all, ISP and backbone censors. Any time an IP blacklist
is being used, TCP/IP Header Identification is probably the technique
being used to match the request against the blacklist. The examples
of TCP/IP Header Identification are too numerous to enumerate in any
meaningful way.
3.3.2. Protocol Identification
Protocol identification is a network analysis technique where one
attempts to identify the protocols being used based on a variety of
traffic characteristics. There have been a number well documented
cases where traffic identification has been used to filter
undesirable protocols. A very simple example of traffic
identification would be to recognize all TCP traffic over port 80 as
HTTP, but much more sophisticated methods, such as analyzing
statistical properties of payload data and flow behavior, have been
used [ref-16][ref-17]. Trade-offs: Protocol Identification
necessarily only provides insight into the way information is
traveling, and not the information itself. This can lead to massive
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overblocking problems if used with popular protocols. Most often
undesirable protocols are those which can be used to transmit
information that is otherwise hard to analyze or considered to likely
cary undesirable information; VoIP, P2P, SSL, and Tor have all been
targets of protocol identification in the past. As statistical
analysis is used, the methods tend to be expensive, both
computationally and financially, and are occasionally imprecise and
under-filter obfuscated protocols. Empirical Examples: Protocol
Identification is easy to prove given the ubiquitous nature of the
throttling/interruption; If only a specific protocol(s) are being
prevented, then Protocol Identification is the most likely culprit.
Iran censors have used Protocol Identification to identify and
throttle SSH traffic by such a large amount as to make it unusable
[ref-18]. The method used by censors in China to identify Tor
connections could also be viewed as a type of Protocol
Identification[ref-19]. Protocol Identification has also been used
by industry from traffic management, such as the 2007 case where
Comcast in the United States was using RST injection to interrupt
BitTorrent Traffic [ref-20].
4. Technical Prevention
4.1. 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 overblocking all content
from otherwise allowable IP's 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 [ref-21]. 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 prevention 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 uses packet dropping as one of its primary
mechanisms of technical censorship [ref-22]. Iran also uses Packet
Dropping as the mechanisms for throttling SSH [ref-23]. These are
but two examples of a ubiquitous censorship practice.
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4.2. RST Packet Injection
Packet injection, generally, refers to a 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: RST Packet Injection has a few
advantages that make it extremely popular is a censorship technique.
RST Packet Injection is an out-of-band prevention 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[ref-24]. 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[ref-25]. 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 sequence number. Sequence
number is the hardest to get correct, as RFC 793 specifies an RST
Packet should be in-sequence to be accepted, although the RFC also
recommends allowing in-window packets as "good enough"[ref-26]. This
in-window recommendation is important, as if it is implement it
allows for successful Blind RST Injection attacks[ref-27]. 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 BitTorrent
[ref-28], this later led to a FCC ruling against Comcast [ref-29].
China has also been known to use RST Packet Injection for censorship
purposes. This prevention is especially evident in the interruption
of encrypted/obfuscated protocols, such as those used by Tor
[ref-30].
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4.3. DNS Cache Poisoning
DNS Cache Poisoning refers to a mechanism where a censor interferes
with the response sent by a DNS resolver to the requesting device by
injecting an alternative IP address on the return path. Cache
poisoning occurs after the requested site's name servers resolve the
request and attempt to forward the IP back to the requesting device;
on the return route the resolved IP is recursively cached by each DNS
servers that initially forwarded the request. During this caching
process if an undesirable keyword is recognized, the resolved IP is
poisoned and an alternative IP is returned. These alternative IP's
usually direct to a nonsense domain or a warning page[ref-31].
Alternatively, Iranian censorship appears to prevent the
communication en-route, preventing a response from ever being
sent[ref-32]. Trade-offs: DNS Cache Poisoning is one of the rarer
forms of prevention due to a number of shortcomings. DNS Cache
Poisoning requires the censor to force a user to traverse a
controlled DNS resolver for the mechanism to be effective, it is
easily circumvented by a technical savvy user that opts to use
alternative DNS resolvers, such as the 8.8.8.8/8.8.4.4 public DNS
resolvers provided by Google. DNS Cache Poisoning also implies
returning an incorrect IP to those attempting to resolve a domain
name, but the site is still technically unblocked if the user has
another method to acquire the IP address of the desired site.
Blocking overflow has also been a problem, as occasionally users
outside of the censors region will be directed through a DNS server
controlled by a censor, causing the request to fail. The ease of
circumvention paired with the large risk of overblocking and blocking
overflow make DNS Cache Poisoning a partial, difficult, and less than
ideal censorship mechanism. Empirical Evidence: DNS Cache Poisoning,
when properly implemented, is easy to identify based on the
shortcomings identified above. Turkey relied on DNS Cache Poisoning
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 ISP's
implementing an IP blacklist to achieve the governmental
mandate[ref-33]. To drive proverbial "nail in the coffin" Turkish
ISPs started hijacking all requests to Google and Level 3's
international DNS resolvers [ref-34]. DNS Cache Poisoning, when
incorrectly implemented, has as 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 Cache Poisoning
attempt; this incident is thought to be the largest internet-service
outage in history [ref-35][ref-36]. 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
[ref-37].
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4.4. Distributed Denial of Service (DDoS)
Distributed Denial of Service attacks are a common attack mechanism
used by "hacktivists" and black-hat hackers, but censors have used
DDoS in the past for a variety of reasons. There is a huge variety
of DDoS attacks[ref-38], 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 [ref-39][ref-40]. Dissenting opinion
websites are frequently victims of DDoS around politically sensitive
events in Burma [ref-41]. Controlling parties in Russia[ref-42],
Zimbabwe[ref-43], and Malaysia[ref-44] have been accused of using
DDoS to interrupt opposition support and access during elections.
4.5. Network Disconnection or Adversarial Route Announcement
Network Disconnection or Adversarial Route Announcement 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 cut off in
a region when a censoring body withdraws all of the 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 [ref-45]. China disconnected the network
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in the Xinjiang region during unrest in 2009 in an effort to prevent
the protests from spreading to other regions [ref-46]. The Arab
Spring saw the the most frequent usage of Network Disconnection, with
events in Egypt and Libya in 2011 [ref-47][ref-48], and Syria in 2012
[ref-49].
5. Non-Technical Aggregation
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 blacklists in that is 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 [ref-50]; more commonly manual filtering
occurs on an institutional level. ICP's, 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 on Self-discipline for
the Chinese Internet Industry". The failure to " energetically
uphold" the pledged values can lead to the ICP's being held liable
for the offending content by the Chinese government [ref-51].
6. Non-Technical Prevention
6.1. Self Censorship
Self censorship is one of the most interesting and effective types of
censorship; a mix of Bentham's Panopticon, cultural manipulation,
intelligence gathering, and meatspace 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 tracing 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[ref-52][ref-53][ref-54][ref-55][ref-56]. A good example of
swaying public thought is China's "50-Cent Party", composed of
somewhere between 20,000[ref-57] and 300,000[ref-58] contributors who
are paid to "guide public thought" on local and regional issues as
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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 [ref-59].
6.2. Domain Name Reallocation
As Domain Names are resolved recursively, if a TLD deregisters a
domain all other DNS resolvers will be unable to properly forward and
cache the site. Domain name registration is only really a risk where
undesirable content is hosted on TLD controlled by the censoring
country, such as .ch or .ru [ref-60].
6.3. 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 [ref-61].
7. References
[ref-1] Glanville, J., ""The Big Business of Net Censorship"",
November 2008 ,
<http://www.theguardian.com/commentisfree/2008/nov/17/
censorship-internet>.
[ref-2] Dalek, J., ""A Method for Identifying and Confirming the
Use of URL Filtering Products for Censorship"", October
2013 , <http://www.cs.stonybrook.edu/~phillipa/papers/
imc112s-dalek.pdf>.
[ref-3] EF, A., ""EFA Filtering Overview"", May 2009 ,
<https://www.efa.org.au/main/wp-content/uploads/2009/05/
efa-filtering-fact-sheets.pdf>.
[ref-4] Crandall, J., ""Empirical Study of a National-Scale
Distributed Intrusion Detection System: Backbone-Level
Filtering of HTML Responses in China"", June 2010 ,
<http://www.cs.unm.edu/~crandall/icdcs2010.pdf >.
[ref-5] Dobie, M., ""Junta Tightens Military Screws"", September
2007 ,
<http://news.bbc.co.uk/2/hi/asia-pacific/7016238.stm>.
[ref-6] Cheng, J., ""Google stops Hong Kong auto-redirect as China
plays hardball"", June 2010, <http://arstechnica.com/tech-
policy/2010/06/
google-tweaks-china-to-hong-kong-redirect-same-results/>.
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[ref-7] Zhu, T., ""An Analysis of Chinese Search Engine
Filtering"", July 2011 , <http://arxiv.org/ftp/arxiv/
papers/1107/1107.3794.pdf#page=10>.
[ref-8] Whittaker, Z., ""1,168 keywords Skype uses to censor,
monitor its Chinese users"", March 2013 ,
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Authors' Addresses
Joeseph L. Hall
Center for Democracy and Technology
Email: jhall@cdt.org
Michael D. Aaron
Center for Democracy and Technology
Email: maaron@cdt.org
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