Network Working Group                                            J. Hall
Internet-Draft                                                       CDT
Intended status: Informational                                  M. Aaron
Expires: November 26, 2018                                    CU Boulder
                                                                B. Jones
                                                             N. Feamster
                                                            May 25, 2018

              A Survey of Worldwide Censorship Techniques


   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
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   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 November 26, 2018.

Copyright Notice

   Copyright (c) 2018 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
   ( in effect on the date of

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   publication of this document.  Please review these documents
   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  . . . . . . . . . . . . . . . . . . . . . . . .   2
   2.  Technical Prescription  . . . . . . . . . . . . . . . . . . .   3
   3.  Technical Identification  . . . . . . . . . . . . . . . . . .   3
     3.1.  Points of Control . . . . . . . . . . . . . . . . . . . .   4
     3.2.  Application Layer . . . . . . . . . . . . . . . . . . . .   5
       3.2.1.  HTTP Request Header Identification  . . . . . . . . .   5
       3.2.2.  HTTP Response Header Identification . . . . . . . . .   6
       3.2.3.  Instrumenting Content Providers . . . . . . . . . . .   6
       3.2.4.  Deep Packet Inspection (DPI) Identification . . . . .   8
       3.2.5.  Server Name Indication  . . . . . . . . . . . . . . .   9
     3.3.  Transport Layer . . . . . . . . . . . . . . . . . . . . .   9
       3.3.1.  TCP/IP Header Identification  . . . . . . . . . . . .   9
       3.3.2.  Protocol Identification . . . . . . . . . . . . . . .  10
   4.  Technical Interference  . . . . . . . . . . . . . . . . . . .  11
     4.1.  Performance Degradation . . . . . . . . . . . . . . . . .  11
     4.2.  Packet Dropping . . . . . . . . . . . . . . . . . . . . .  12
     4.3.  RST Packet Injection  . . . . . . . . . . . . . . . . . .  12
     4.4.  DNS Interference  . . . . . . . . . . . . . . . . . . . .  14
     4.5.  Distributed Denial of Service (DDoS)  . . . . . . . . . .  16
     4.6.  Network Disconnection or Adversarial Route Announcement .  16
   5.  Non-Technical Prescription  . . . . . . . . . . . . . . . . .  17
   6.  Non-Technical Interference  . . . . . . . . . . . . . . . . .  17
     6.1.  Self Censorship . . . . . . . . . . . . . . . . . . . . .  17
     6.2.  Domain Name Reallocation  . . . . . . . . . . . . . . . .  18
     6.3.  Server Takedown . . . . . . . . . . . . . . . . . . . . .  18
     6.4.  Notice and Takedown . . . . . . . . . . . . . . . . . . .  18
   7.  Contributors  . . . . . . . . . . . . . . . . . . . . . . . .  19
   8.  Informative References  . . . . . . . . . . . . . . . . . . .  19
   Authors' Addresses  . . . . . . . . . . . . . . . . . . . . . . .  28

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.  (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.)

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   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).

   We describe three elements of Internet censorship: prescription,
   identification, and interference.  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
   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 "to block"
   information in blacklists or using real-time heuristic assessment of
   content [Ding-1999].

   There are typically three types 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 using routing data in TCP/IP headers.  The mechanisms for
   building up these blacklists are varied.  Censors can 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, thes private
   services attempt to categorize every semi-questionable website as to
   allow for metatag 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 or the Ministry of Culture and
   Islamic Guidance in Iran, which maintain their own blacklists.

3.  Technical Identification

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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 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.

   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

   o  Certificate Authorities: Authorities that issue cryptographically
      secured resources can be a significant point of control.

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      Certificate Authorities that issue certificates to domain holders
      for TLS/HTTPS or Regional/Local Internet Registries that issue
      Route Origination Authorizations to BGP operators can be forced to
      issue rogue certificates that may allow compromises in
      confidentiatlity guarantees - allowing censorship software to
      engage in identification and interference where not possible
      before - or integrity degrees - 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 improve quality of service.  These can
      be powerful points of control for censors, especially if the
      location of a CDN results in easier interference.

   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 impair
   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

   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, 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.  However, some countermeasures such

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   as URL obfuscation [RSF-2005] can trivially defeat simple forms of
   HTTP Request Header Identification.

   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
   [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]

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) 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 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

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   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 [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 is based on laws and
   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 [Cheng-2010].  It is clear these blacklists
   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 100,00 queries in U.K.
   to help combat abuse [BBC-2013] [Condliffe-2013].

   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

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   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 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

   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.  (TODO: talk about content
   inference through things like TLS fingerprinting?)

   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 [Crandall-2010]
   [Clayton-2006] [Anonymous-2014].

   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 [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 obsf2
   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

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   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].

3.2.5.  Server Name Indication

   In encrypted connections using Transport Layer Security (TLS), there
   may be servers that host multiple "virtual servers" at a give 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., may be censored while is not) [Shbair-2015].
   (TODO: talk about domain fronting in CDNs where SNI does not match
   the HOST field inside the encrypted HTTPS envelope?)

   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 is inadvertently blocked.

   Empirical Evidence: While there are many examples of security firms
   that offer SNI-based filtering [Trustwave-2015] [Sophos-2015]
   [Shbair-2015], the authors currently know of no specific examples or
   reports of SNI-based filtering observed in the field used for
   censorship purposes.

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.

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   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.

   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
   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.

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

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   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 [Winter-2012].

   Trade-offs: Protocol Identification necessarily only provides insight
   into the way information is traveling, and not the information

   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
   statistical analysis, and can be ineffective due to its imprecise

   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

4.  Technical Interference

   (TODO: organize this section into layers just like identification
   above.  Alternatively, the whole document can be organized in a layer
   structure and do identification and interference at the same time for
   each layer?  That seems wise.)

4.1.  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
   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

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   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 is known to shape the bandwidth available to
   HTTPS traffic to encourage unencrypted HTTP traffic [Aryan-2012].

4.2.  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 overblocking 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 uses packet dropping as one of its
   primary mechanisms of technical censorship [Ensafi-2013].  Iran also
   uses Packet Dropping as the mechanisms for throttling SSH
   [Aryan-2012].  These are but two examples of a ubiquitous censorship

4.3.  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

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   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 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
   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].

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4.4.  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

   "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 the Chinese network does (we
   are not aware of any other wide-scale uses of mangling).  On the
   Chinese network 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 a censored
   name, there will be no response.  If it is censored, an erroneous
   response will be returned.  For example, using the command-line dig
   utility to query an unused IP address in China of for
   the name "" (uncensored at the time of writing) compared
   with "" (censored at the time of writing), we get an
   erroneous IP address "" as a response:

   % dig +short +nodnssec @ A
   ;; connection timed out; no servers could be reached

   % dig +short +nodnssec @ A

   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 resursive resolver such as an Internet access provider
   - be different than what authoritative resolvers would provide

   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 [ViewDNS-2011].
   (TODO: Stephane says this cite misuses "cache poisoning" and that we
   haven't seen much of this performed systematically.)  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

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   quickly than the upstream resolver can respond, causing an erroneous
   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

   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 a technical savvy user that
   opts to use alternative DNS resolvers (such as the public DNS
   resolvers provided by Google, OpenDNS, Telcomix, or FDN) or Virtual
   Private Network 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
   access it if the site is configured to be the default server
   listening at this IP address.  Blocking overflow 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 overblocking and blocking
   overflow make DNS interference a partial, difficult, and less than
   ideal censorship mechanism.

   Empirical Evidence: 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 blacklist to achieve
   the governmental mandate [Zmijewki-2014].  Ultimately, Turkish ISPs
   started hijacking all requests to Google and Level 3's international
   DNS resolvers [Zmijewki-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,, 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].

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4.5.  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 colocated with
   the Great Firewall, dubbed "Great Cannon", that was able to inject
   JavaScript code into web visits to a Chinese search engine that
   comandeered those user agents to send DDoS traffic to various sites

4.6.  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.

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   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

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 blacklists 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
   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

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, 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

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   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
   [Calamur-2013] [AP-2012] [Hopkins-2011] [Guardian-2014]
   [Johnson-2010].  A good example of swaying public thought is China's
   "50-Cent Party", 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.  Domain Name Reallocation

   As Domain Names are resolved recursively, if a TLD deregisters a
   domain all other DNS servers 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 .cn or .ru [Anderson-2011] or where legal processes
   in countries like the United States result in domain name seizures
   and/or DNS redirection by the government [Kopel-2013].

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 [Anderson-2011].

6.4.  Notice and Takedown

   In some countries, legal mechanisms exist where an individual can
   issue a legal request to a content host that requires the host to
   take down content.  Examples include the voluntary systems employed
   by companies like Google to comply with "Right to be Forgotten"
   policies in the European Union [Google-RTBF] and the copyright-
   oriented notice and takedown regime of the United States Digital
   Millennium Copyright Act (DMCA) Section 512 [DMLP-512].

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7.  Contributors

   This document benefited from discussions with Stephane Bortzmeyer,
   Nick Feamster, and Martin Nilsson.

8.  Informative References

              AFNIC, "Report of the AFNIC Scientific Council:
              Consequences of DNS-based Internet filtering", 2013,

              AFP, "China Has Massive Internet Breakdown Reportedly
              Caused By Their Own Censoring Tools", 2014,

              Albert, K., "DNS Tampering and the new ICANN gTLD Rules",
              2011, <

              Anderson, R. and S. Murdoch, "Access Denied: Tools and
              Technology of Internet Filtering", 2011,

              Anonymous, "The Collateral Damage of Internet Censorship
              by DNS Injection", 2012,

              Anonymous, "How to Bypass Comcast's Bittorrent
              Throttling", 2012, <

              Anonymous, "GitHub blocked in China - how it happened, how
              to get around it, and where it will take us", 2013,

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              Anonymous, "Towards a Comprehensive Picture of the Great
              Firewall's DNS Censorship", 2014,

   [AP-2012]  Associated Press, "Sattar Beheshit, Iranian Blogger, Was
              Beaten In Prison According To Prosecutor", 2012,

              Aryan, S., Aryan, H., and J. Halderman, "Internet
              Censorship in Iran: A First Look", 2012,

              BBC News, "Google and Microsoft agree steps to block abuse
              images", 2013, <>.

              BBC, "China employs two million microblog monitors state
              media say", 2013,

              Bortzmayer, S., "DNS Censorship (DNS Lies) As Seen By RIPE
              Atlas", 2015,

              Bristow, M., "China's internet 'spin doctors'", 2013,

              Calamur, K., "Prominent Egyptian Blogger Arrested", 2013,

              CERT, "TCP SYN Flooding and IP Spoofing Attacks", 2000,

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              Cheng, J., "Google stops Hong Kong auto-redirect as China
              plays hardball", 2010, <

              Clayton, R., "Ignoring the Great Firewall of China", 2006,

              Condliffe, J., "Google Announces Massive New Restrictions
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              Cowie, J., "Egypt Leaves the Internet", 2011,

              Cowie, J., "Libyan Disconnect", 2011,

              Crandall, J., "Empirical Study of a National-Scale
              Distributed Intrusion Detection System: Backbone-Level
              Filtering of HTML Responses in China", 2010,

              Dalek, J., "A Method for Identifying and Confirming the
              Use of URL Filtering Products for Censorship", 2013,

              Ding, C., Chi, C., Deng, J., and C. Dong, "Centralized
              Content-Based Web Filtering and Blocking: How Far Can It
              Go?", 1999, <

              Digital Media Law Project, "Protecting Yourself Against
              Copyright Claims Based on User Content", 2012,

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              Dobie, M., "Junta tightens media screw", 2007,

              Ensafi, R., "Detecting Intentional Packet Drops on the
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              Fareed, M., "China joins a turf war", 2008,

              Gao, H., "Tiananmen, Forgotten", 2014,

              Glanville, J., "The Big Business of Net Censorship", 2008,

              Google, Inc., "Search removal request under data
              protection law in Europe", 2015,

              The Gaurdian, "Chinese blogger jailed under crackdown on
              'internet rumours'", 2014,

              Heacock, R., "China Shuts Down Internet in Xinjiang Region
              After Riots", 2009, <

              Electronic Frontier Foundation, "Hepting vs. AT&T", 2011,

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              Hjelmvik, E., "Breaking and Improving Protocol
              Obfuscation", 2010,

              Hopkins, C., "Communications Blocked in Libya, Qatari
              Blogger Arrested: This Week in Online Tyranny", 2011,

              ICANN Security and Stability Advisory Committee (SSAC),
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              the Domain Name System", 2012,

              Johnson, L., "Torture feared in arrest of Iraqi blogger",
              2011, <

              Jones, B., "Automated Detection and Fingerprinting of
              Censorship Block Pages", 2014,

              Khattak, S., "Towards Illuminating a Censorship Monitor's
              Model to Facilitate Evasion", 2013, <http://0b4af6cdc2f0c5

              Kopel, K., "Operation Seizing Our Sites: How the Federal
              Government is Taking Domain Names Without Prior Notice",
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              Kravtsova, Y., "Cyberattacks Disrupt Opposition's
              Election", 2012,

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              Marczak, B., Weaver, N., Dalek, J., Ensafi, R., Fifield,
              D., McKune, S., Rey, A., Scott-Railton, J., Deibert, R.,
              and V. Paxson, "An Analysis of China's "Great Cannon"",

              Muncaster, P., "Malaysian election sparks web blocking/
              DDoS claims", 2013,

              Nabi, Z., "The Anatomy of Web Censorship in Pakistan",
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              n3t2.3c, "TCP-RST Injection", 2011,

              Orion, E., "Zimbabwe election hit by hacking and DDoS
              attacks", 2013,

              Porter, T., "The Perils of Deep Packet Inspection", 2010,

   [RFC0793]  Postel, J., "Transmission Control Protocol", STD 7,
              RFC 793, DOI 10.17487/RFC0793, September 1981,

   [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,

   [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, <>.

              Reporters Sans Frontieres, "Technical ways to get around
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              Sandvine, "Technology Showcase on Traffic Classification:
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              Schoen, S., "EFF tests agree with AP: Comcast is forging
              packets to interfere with user traffic", 2007,

              Schone, M., Esposito, R., Cole, M., and G. Greenwald,
              "Snowden Docs Show UK Spies Attacked Anonymous, Hackers",
              2014, <

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              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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              Sophos, "Understanding Sophos Web Filtering", 2015,

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              Trustwave, "Filter: SNI extension feature and HTTPS
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    , "DNS Cache Poisoning in the People's
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              Villeneuve, N., "Open Access: Chapter 8, Control and
              Resistance, Attacks on Burmese Opposition Media", 2011,

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              VonLohmann, F., "FCC Rules Against Comcast for BitTorrent
              Blocking", 2008, <

              Wagner, B., "Deep Packet Inspection and Internet
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              Wagstaff, J., "In Malaysia, online election battles take a
              nasty turn", 2013,

              Weaver, N., Sommer, R., and V. Paxson, "Detecting Forged
              TCP Packets", 2009, <

              Whittaker, Z., "1,168 keywords Skype uses to censor,
              monitor its Chinese users", 2013,

              Wikipedia, "Denial of Service Attacks", 2016,

              Wilde, T., "Knock Knock Knockin' on Bridges Doors", 2012,

              Winter, P., "How China is Blocking Tor", 2012,

              Zhu, T., "An Analysis of Chinese Search Engine Filtering",

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              Zmijewki, E., "Turkish Internet Censorship Takes a New
              Turn", 2014, <

Authors' Addresses

   Joseph Lorenzo Hall


   Michael D. Aaron
   CU Boulder


   Ben Jones


   Nick Feamster


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