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NETWORK WORKING GROUP                                            J. Hall
Internet-Draft                                                       CDT
Intended status: Informational                                  M. Aaron
Expires: October 30, 2015                                     CU Boulder
                                                                B. Jones
                                                                 GA Tech
                                                          April 28, 2015


              A Survey of Worldwide Censorship Techniques
                     draft-hall-censorship-tech-01

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.

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
   working documents as Internet-Drafts.  The list of current Internet-
   Drafts is at http://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 October 30, 2015.

Copyright Notice

   Copyright (c) 2015 IETF Trust and the persons identified as the
   document authors.  All rights reserved.

   This document is subject to BCP 78 and the IETF Trust's Legal
   Provisions Relating to IETF Documents
   (http://trustee.ietf.org/license-info) in effect on the date of
   publication of this document.  Please review these documents



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   carefully, as they describe your rights and restrictions with respect
   to this document.  Code Components extracted from this document must
   include Simplified BSD License text as described in Section 4.e of
   the Trust Legal Provisions and are provided without warranty as
   described in the Simplified BSD License.


Table of Contents

   1.  Introduction . . . . . . . . . . . . . . . . . . . . . . . . .  3
   2.  Technical Aggregation  . . . . . . . . . . . . . . . . . . . .  4
   3.  Technical Identification . . . . . . . . . . . . . . . . . . .  5
     3.1.  Points of Control  . . . . . . . . . . . . . . . . . . . .  5
     3.2.  Application Layer  . . . . . . . . . . . . . . . . . . . .  6
       3.2.1.  HTTP Request Header Identification . . . . . . . . . .  6
       3.2.2.  HTTP Response Header Identification  . . . . . . . . .  6
       3.2.3.  Instrumenting Content Providers  . . . . . . . . . . .  7
       3.2.4.  Deep Packet Inspection (DPI) Identification  . . . . .  8
     3.3.  Transport Layer  . . . . . . . . . . . . . . . . . . . . .  9
       3.3.1.  TCP/IP Header Identification . . . . . . . . . . . . .  9
       3.3.2.  Protocol Identification  . . . . . . . . . . . . . . . 10
   4.  Technical Prevention . . . . . . . . . . . . . . . . . . . . . 12
     4.1.  Packet Dropping  . . . . . . . . . . . . . . . . . . . . . 12
     4.2.  RST Packet Injection . . . . . . . . . . . . . . . . . . . 12
     4.3.  DNS Cache Poisoning  . . . . . . . . . . . . . . . . . . . 13
     4.4.  Distributed Denial of Service (DDoS) . . . . . . . . . . . 14
     4.5.  Network Disconnection or Adversarial Route Announcement  . 15
   5.  Non-Technical Aggregation  . . . . . . . . . . . . . . . . . . 16
   6.  Non-Technical Prevention . . . . . . . . . . . . . . . . . . . 17
     6.1.  Self Censorship  . . . . . . . . . . . . . . . . . . . . . 17
     6.2.  Domain Name Reallocation . . . . . . . . . . . . . . . . . 17
     6.3.  Server Takedown  . . . . . . . . . . . . . . . . . . . . . 17
   7.  References . . . . . . . . . . . . . . . . . . . . . . . . . . 18
   Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . . 24

















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1.  Introduction

   This document describes the technical mechanisms used by censorship
   regimes around the world to block or degrade internet traffic.  To
   that end, we describe three elements of Internet censorship:
   aggregation, identification, and prevention.  Aggregation is the
   process by which censors determine what they should block, i.e. they
   decide to block a list of pornographic websites.  Identification is
   the process by which censors determine whether content is blocked,
   i.e. the censor blocks all webpages containing "sex" in the title.
   Prevention is the process by which the censor intercedes in
   communication and prevents access to censored materials.







































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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 [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.
































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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
      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



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   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

   An HTTP header contains a lot of useful information for traffic
   identification; although host is the only required field in an HTTP
   request header, an 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.  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.

   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
   [58][59][60].  Commercial technologies such as the McAfee SmartFilter
   and NetSweeper are often purchased by censors [2].  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
   [2][61].

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.



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   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) used
   this technique [3].  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 Providers

   In addition to censorship by the state, many governments pressure
   content providers to censor themselves.  Due to the extensive reach
   of government censorship, we need to define content provider as any
   service that provides utility to users, including everything from web
   sites to locally installed programs.  The defining factor of keyword
   identification by content providers is the choice of content
   providers to detect restricted terms on their platform.  The terms to
   look for may be provided by the government or the content provider
   may be expected to come up with their own list.

   Tradeoffs: By instrumenting content providers to identify restricted
   content, 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, but this may drive away potential investment.
   Coercing content providers may encourage self censorship, an
   additional advantage for censors.  The tradeoffs for instrumenting
   content providers are highly dependent on the content provider and
   the requested assistance.

   Empirical Examples: Researchers have discovered keyword
   identification by content providers on platforms ranging from instant
   messaging applications [63] to search engines [62][4][6][7][8].  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 is based on laws and



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   regulations of the country a search engine is operating in.  The
   keyword blacklists are most likely maintained by the search engine
   provider.  China requires search engine providers to "voluntarily"
   maintain search term blacklists to acquire/keep an Internet content
   provider (ICP) license [4].  It is clear these blacklists are
   maintained by each search engine provider based on the slight
   variations in the intercepted searches [5][6].  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
   [7][8].

   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, Microsoft's
   search engine, Bing, was accussed of censoring Chinese content
   outside of China [62] 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.

3.2.4.  Deep Packet Inspection (DPI) Identification

   Deep Packet Inspection has become computationally feasible as a
   censorship mechanism in the past 5 years [9].  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 [10].  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



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   communication) to identify traffic.

   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, uses DPI to
   identify restricted content over HTTP and DNS and inject TCP RSTs and
   bad DNS responses, respectively, into connections [3][64][65].

   Empirical Evidence: 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 [3][64][65][66].  The Tor project claims
   that China, Iran, Ethiopia, and others must being using DPI to block
   the obsf2 protocol [11].  Malaysia has been accused of using targeted
   DPI, paired with DDoS, to identify and subsequently knockout pro-
   opposition material [12].  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 [13].

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 censor to 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.

   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.  Blacklisting an IP is equivalent to
   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.



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   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 whitelisting is
   occasionally used, where a censor limits communication to approved
   ports, such as 80 for HTTP traffic and is most effective when used in
   conjuction 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.

3.3.2.  Protocol Identification

   Censors sometimes identify entire protocols to be blocked using a
   variety of traffic characteristics.  For example, Iran degrades the
   performance of HTTPS traffic, a procotol that prevents further
   analysis, to encourage users to switch to HTTP, a protocol that they
   can analyze [60].  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 [14][15].

   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
   is running a circumvention tool.  China has used active scanning to
   great effect to block Tor [17].

   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 overblocking
   problems when used with popular protocols.  These methods are
   expensive, both computationally and financially, due to the use of



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   statistical analysis, and can be ineffective due to its 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 [16] and by China to identify and block Tor relays [17].
   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 [17].







































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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 [18].  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 [19].  Iran also uses Packet
   Dropping as the mechanisms for throttling SSH [20].  These are but
   two examples of a ubiquitous censorship practice.

4.2.  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: 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



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   inspect a copy of the information, usually mirrored by an optical
   splitter, making it an ideal pairing for DPI and Protocol
   Identification [21].  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 [22].  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 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" [23].  This
   in-window recommendation is important, as if it is implement it
   allows for successful Blind RST Injection attacks [24].  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 [25], this later led to a US Fderal Communications
   Commission ruling against Comcast [26].  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 [27].

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 into the response message 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 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 is returned.  These
   alternative IP's usually direct to a nonsense domain or a warning
   page [28].  Alternatively, Iranian censorship appears to prevent the
   communication en-route, preventing a response from ever being sent



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   [29].

   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 [30].  To drive
   proverbial "nail in the coffin" Turkish ISPs started hijacking all
   requests to Google and Level 3's international DNS resolvers [31].
   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 [32][33].
   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 [34].

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 [35], 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.




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   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 [36][37].  Dissenting opinion
   websites are frequently victims of DDoS around politically sensitive
   events in Burma [38].  Controlling parties in Russia [39], Zimbabwe
   [40], and Malaysia [41] have been accused of using DDoS to interrupt
   opposition support and access during elections.

4.5.  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
   [42].  China disconnected the network in the Xinjiang region during
   unrest in 2009 in an effort to prevent the protests from spreading to
   other regions [43].  The Arab Spring saw the the most frequent usage
   of Network Disconnection, with events in Egypt and Libya in 2011
   [44][45], and Syria in 2012 [46].





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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 [47]; more commonly manual filtering
   occurs on an institutional level.  (Internet Content Provider?)
   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 [47].

































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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
   [48][49][50][51][52].  A good example of swaying public thought is
   China's "50-Cent Party", composed of somewhere between 20,000 [53]
   and 300,000 [54] 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 [55].

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 [56].

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 [57].











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7.  References

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         January 2012, <https://blog.torproject.org/blog/
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   [23]  Weaver, S., "Detecting Forged TCP Packets", June 2009 ,



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         <http://www.icir.org/vern/papers/reset-injection.ndss09.pdf>.

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   [26]  VonLohmann, F., "FCC Rules Against Comcast for BitTorrent
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   [27]  Phillip Winter, S., "How China Is Blocking Tor", April 2nd,,
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   [28]  DNS, V., "DNS Cache Poisoning in the People's Republic of
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   [30]  Zmijewki, E., "Turkish Internet Censorship Takes a New Turn",
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   [31]  Zmijewki, E., "Turkish Internet Censorship Takes a New Turn",
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   [32]  AFP,  ., "China Has Massive Internet Breakdown Reportedly
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         2014-1>.

   [33]  Anonymous, A., "The Collateral Damage of Internet Censorship by
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   [34]  Albert, K., "DNS Tampering and the new ICANN gTLD Rules",
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   [35]  Anonymous, A., "Denial of Service Attacks (Wikipedia)"", N/A



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          N/A, <http://en.wikipedia.org/wiki/
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   [40]  Orion, E., "Zimbabwe election hit by hacking and DDoS attacks",
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   [46]  Thomson, I., "Syria Cuts off Internet and Mobile
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   [47]  News, B., "China employs two million microblog monitors state



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         media say", October 2013,
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   [59]  Nabi, Z., "The Anatomy of Web Censorship in Pakistan",
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Authors' Addresses

   Joseph L. Hall
   CDT

   Email: jhall@cdt.org


   Michael D. Aaron
   CU Boulder

   Email: michael.aaron@colorado.edu


   Ben Jones
   GA Tech

   Email: bjones99@gatech.edu

































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