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Versions: (draft-hall-censorship-tech) 00 01 02 03

pearg                                                            J. Hall
Internet-Draft                                          Internet Society
Intended status: Informational                                  M. Aaron
Expires: November 19, 2020                                    CU Boulder
                                                                S. Adams
                                                         A. Andersdotter

                                                                B. Jones
                                                             N. Feamster
                                                               U Chicago
                                                            May 18, 2020

              A Survey of Worldwide Censorship Techniques


   This document describes technical mechanisms censorship regimes
   around the world use for blocking or impairing Internet traffic.  It
   aims to make designers, implementers, and users of Internet protocols
   aware of the properties exploited and mechanisms used for censoring
   end-user access to information.  This document makes no suggestions
   on individual protocol considerations, and is purely informational,
   intended as 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 https://datatracker.ietf.org/drafts/current/.

   Internet-Drafts are draft documents valid for a maximum of six months
   and may be updated, replaced, or obsoleted by other documents at any
   time.  It is inappropriate to use Internet-Drafts as reference
   material or to cite them other than as "work in progress."

   This Internet-Draft will expire on November 19, 2020.

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Copyright Notice

   Copyright (c) 2020 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
   (https://trustee.ietf.org/license-info) in effect on the date of
   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  . . . . . . . . . . . . . . . . . . . . . . . .   3
     1.1.  Terminology . . . . . . . . . . . . . . . . . . . . . . .   3
   2.  Technical Prescription  . . . . . . . . . . . . . . . . . . .   3
   3.  Technical Identification  . . . . . . . . . . . . . . . . . .   4
     3.1.  Points of Control . . . . . . . . . . . . . . . . . . . .   4
     3.2.  Application Layer . . . . . . . . . . . . . . . . . . . .   6
       3.2.1.  HTTP Request Header Identification  . . . . . . . . .   6
       3.2.2.  HTTP Response Header Identification . . . . . . . . .   7
       3.2.3.  Instrumenting Content Distributors  . . . . . . . . .   7
       3.2.4.  Deep Packet Inspection (DPI) Identification . . . . .   9
     3.3.  Transport Layer . . . . . . . . . . . . . . . . . . . . .  11
       3.3.1.  Shallow Packet Inspection and Transport Header
               Identification  . . . . . . . . . . . . . . . . . . .  11
       3.3.2.  Protocol Identification . . . . . . . . . . . . . . .  12
   4.  Technical Interference  . . . . . . . . . . . . . . . . . . .  14
     4.1.  Application Layer . . . . . . . . . . . . . . . . . . . .  14
       4.1.1.  DNS Interference  . . . . . . . . . . . . . . . . . .  14
     4.2.  Transport Layer . . . . . . . . . . . . . . . . . . . . .  16
       4.2.1.  Performance Degradation . . . . . . . . . . . . . . .  16
       4.2.2.  Packet Dropping . . . . . . . . . . . . . . . . . . .  17
       4.2.3.  RST Packet Injection  . . . . . . . . . . . . . . . .  17
     4.3.  Multi-layer and Non-layer . . . . . . . . . . . . . . . .  18
       4.3.1.  Distributed Denial of Service (DDoS)  . . . . . . . .  18
       4.3.2.  Network Disconnection or Adversarial Route
               Announcement  . . . . . . . . . . . . . . . . . . . .  19
   5.  Non-Technical Prescription  . . . . . . . . . . . . . . . . .  20
   6.  Non-Technical Interference  . . . . . . . . . . . . . . . . .  20
     6.1.  Self-Censorship . . . . . . . . . . . . . . . . . . . . .  20
     6.2.  Server Takedown . . . . . . . . . . . . . . . . . . . . .  21
     6.3.  Notice and Takedown . . . . . . . . . . . . . . . . . . .  21
   7.  Contributors  . . . . . . . . . . . . . . . . . . . . . . . .  21

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   8.  Informative References  . . . . . . . . . . . . . . . . . . .  22
   Authors' Addresses  . . . . . . . . . . . . . . . . . . . . . . .  35

1.  Introduction

   Censorship is where an entity in a position of power - such as a
   government, organization, or individual - suppresses communication
   that it considers objectionable, harmful, sensitive, politically
   incorrect or inconvenient [WP-Def-2020].  Although censors that
   engage in censorship must do so through legal, military, or other
   means, this document focuses largely on technical mechanisms used to
   achieve network censorship.

   This document describes technical mechanisms that censorship regimes
   around the world use for blocking or impairing 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.  There is also a growing field of
   academic study of censorship circumvention (see the review article of
   [Tschantz-2016]), results from which we seek to make relevant here
   for protocol designers and implementers.

1.1.  Terminology

   We describe three elements of Internet censorship: prescription,
   identification, and interference.  The document contains three major
   sections, each corresponding to one of these elements.  Prescription
   is the process by which censors determine what types of material they
   should block, i.e., deciding to block a list of pornographic
   websites.  Identification is the process by which censors classify
   specific traffic to be blocked or impaired, i.e., blocking or
   impairing all webpages containing "sex" in the title or traffic to
   www.sex.example.  Interference is the process by which censors
   intercede in communication and prevents access to censored materials
   by blocking access or impairing the connection.

2.  Technical Prescription

   Prescription is the process of figuring out what censors would like
   to block [Glanville-2008].  Generally, censors aggregate information
   "to block" in blocklists or use real-time heuristic assessment of
   content [Ding-1999].  Some national networks are designed to more
   naturally serve as points of control [Leyba-2019].  There are also
   indications that online censors use probabilistic machine learning
   techniques [Tang-2016].

   There are typically three types of blocklist elements: Keyword,
   domain name, or Internet Protocol (IP) address.  Keyword and domain

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   name blocking take place at the application level, e.g., HTTP,
   whereas IP blocking tends to take place using IP addresses in IPv4/
   IPv6 headers.  The mechanisms for building up these blocklists vary.
   Censors can purchase from private industry "content control"
   software, such as SmartFilter, which lets censors filter traffic from
   broad categories they would like to block, such as gambling or
   pornography [Knight-2005].  In these cases, these private services
   attempt to categorize every semi-questionable website as to allow for
   meta-tag blocking.  Similarly, they tune real-time content heuristic
   systems to map their assessments onto categories of objectionable

   Countries that are more interested in retaining specific political
   control typically have ministries or organizations that maintain
   blocklists.  Examples include the Ministry of Industry and
   Information Technology in China, Ministry of Culture and Islamic
   Guidance in Iran, and specific to copyright in France [HADOPI-2020]
   and across the EU for consumer protection law [Reda-2017].

3.  Technical Identification

3.1.  Points of Control

   Internet censorship necessarily takes place over a network.  Network
   design gives censors a number of different points-of-control where
   they can identify the content they are interested in filtering.  An
   important aspect of pervasive technical interception is the necessity
   to rely on software or hardware to intercept the content the censor
   is interested in.  There are various logical and physical points-of-
   control censors may use for interception mechanisms, including,
   though not limited to, the following.

   o  Internet Backbone: If a censor controls the gateways into a
      region, they can filter undesirable traffic that is traveling into
      and out of the region by packet sniffing and port mirroring at the
      relevant exchange points.  Censorship at this point of control is
      most effective at controlling the flow of information between a
      region and the rest of the Internet, but is ineffective at
      identifying content traveling between the users within a region.
      Some national network designs naturally serve as more effective
      chokepoints and points of control [Leyba-2019].

   o  Internet Service Providers: Internet Service Providers are
      frequently exploited points of control.  They have the benefit of
      being easily enumerable by a censor - often falling under the
      jurisdictional or operational control of a censor in an
      indisputable way - with the additional feature that an ISP can
      identify the regional and international traffic of all their

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      users.  The censor's filtration mechanisms can be placed on an ISP
      via governmental mandates, ownership, or voluntary/coercive

   o  Institutions: Private institutions such as corporations, schools,
      and Internet cafes can use filtration mechanisms.  These
      mechanisms are occasionally at the request of a government censor,
      but can also be implemented to help achieve institutional goals,
      such as fostering a particular moral outlook on life by school-
      children, independent of broader society or government goals.

   o  Content Distribution Networks (CDNs): CDNs seek to collapse
      network topology in order to better locate content closer to the
      service's users.  This reduces content transmission latency and
      improves quality of service.  The CDN service's content servers,
      located "close" to the user in a network-sense, can be powerful
      points of control for censors, especially if the location of CDN
      content repositories allow for easier interference.

   o  Certificate Authorities for Public-Key Infrastructures (PKIs):
      Authorities that issue cryptographically secured resources can be
      a significant point of control.  Certificate Authorities that
      issue certificates to domain holders for TLS/HTTPS (the Web PKI)
      or Regional/Local Internet Registries (RIRs) that issue Route
      Origination Authorizations (ROAs) to BGP operators can be forced
      to issue rogue certificates that may allow compromise, i.e., by
      allowing censorship software to engage in identification and
      interference where not possible before.  This may allow, for
      example, adversarial traffic routing or TLS interception.

   o  Services: Application service providers can be pressured, coerced,
      or legally required to censor specific content or data flows.
      Service providers naturally face incentives to maximize their
      potential customer base and potential service shutdowns or legal
      liability due to censorship efforts may seem much less attractive
      than potentially excluding content, users, or uses of their
      service.  Services have increasingly become focal points of
      censorship discussions, as well as the focus of discussions of
      moral imperatives to use censorship tools.

   o  Personal Devices: Censors can mandate censorship software be
      installed on the device level.  This has many disadvantages in
      terms of scalability, ease-of-circumvention, and operating system
      requirements.  (Of course, if a personal device is treated with
      censorship software before sale and this software is difficult to
      reconfigure, this may work in favor of those seeking to control
      information, say for children, students, customers, or employees.)
      The emergence of mobile devices exacerbate these feasibility

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      problems.  This software can also be mandated by institutional
      actors acting on non-governmentally mandated moral imperatives.

   At all levels of the network hierarchy, the filtration mechanisms
   used to detect undesirable traffic are essentially the same: a censor
   either directly sniffs transmitting packets and identifies
   undesirable content, and then uses a blocking or shaping mechanism to
   prevent or impair access, or requests that an actor ancillary to the
   censor, such as a private entity, perform these functions.
   Identification of undesirable traffic can occur at the application,
   transport, or network layer of the IP stack.  Censors often focus on
   web traffic, so the relevant protocols tend to be filtered in
   predictable ways (see Section 3.2.1 and Section 3.2.2).  For example,
   a subversive image might make it past a keyword filter.  However, if
   later the image is deemed undesirable, a censor may then blacklist
   the provider site's IP address.

3.2.  Application Layer

   The following subsections describe properties and tradeoffs of common
   ways in which censors filter using application-layer information.
   Each subsection includes empirical examples describing these common
   behaviors for further reference.

3.2.1.  HTTP Request Header Identification

   An HTTP header contains a lot of useful information for traffic
   identification.  Although "host" is the only required field in an
   HTTP request header (for HTTP/1.1 and later), an HTTP method field is
   necessary to do anything useful.  As such, "method" and "host" are
   the two fields used most often for ubiquitous censorship.  A censor
   can sniff traffic and identify a specific domain name (host) and
   usually a page name (GET /page) as well.  This identification
   technique is usually paired with transport 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 transport identification (see Section 3.3.1)
   is necessary for HTTPS filtering.  However, some countermeasures such
   can trivially defeat simple forms of HTTP Request Header
   Identification.  For example, two cooperating endpoints - an
   instrumented web server and client - could encrypt or otherwise
   obfuscate the "host" header in a request, potentially thwarting
   techniques that match against "host" header values.

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   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 Transport 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.  However, they are made useless by HTTPS because
   HTTPS encrypts the response and its headers.

   The response fields are also less helpful for identifying content
   than request fields, as "Server" could easily be identified using
   HTTP Request Header identification, and "Via" is rarely relevant.
   HTTP Response censorship mechanisms normally let the first n packets
   through while the mirrored traffic is being processed; this may allow
   some content through and the user may be able to detect that the
   censor is actively interfering with undesirable content.

   Empirical Examples: In 2009, Jong Park et al. at the University of
   New Mexico demonstrated that the Great Firewall of China (GFW) has
   used this technique [Crandall-2010].  However, Jong Park et al. found
   that the GFW discontinued this practice during the course of the
   study.  Due to the overlap in HTTP response filtering and keyword
   filtering (see Section 3.2.3), it is likely that most censors rely on
   keyword filtering over TCP streams instead of HTTP response

3.2.3.  Instrumenting Content Distributors

   Many governments pressure content providers to censor themselves, or
   provide the legal framework within which content distributors are
   incentivized to follow the content restriction preferences of agents
   external to the content distributor [Boyle-1997].  Due to the
   extensive reach of such censorship, we define content distributor as

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   any service that provides utility to users, including everything from
   web sites to locally installed programs.  A commonly used method of
   instrumenting content distributors consists of keyword identification
   to detect restricted terms on their platform.  Governments may
   provide the terms on such keyword lists.  Alternatively, the content
   provider may be expected to come up with their own list.  A different
   method of instrumenting content distributors consists of requiring a
   distributor to disassociate with some categories of users.  See also
   Section 6.3.

   Tradeoffs: By instrumenting content distributors to identify
   restricted content or content providers, the censor can gain new
   information at the cost of political capital with the companies it
   forces or encourages to participate in censorship.  For example, the
   censor can gain insight about the content of encrypted traffic by
   coercing web sites to identify restricted content.  Coercing content
   distributors to regulate users, categories of users, content and
   content providers may encourage users and content providers to
   exhibit self-censorship, an additional advantage for censors (see
   Section 6.1).  The tradeoffs for instrumenting content distributors
   are highly dependent on the content provider and the requested
   assistance.  A typical concern is that the targeted keywords or
   categories of users are too broad, risk being too broadly applied, or
   are not subjected to a sufficiently robust legal process prior to
   their mandatory application (see p. 8 of [EC-2012]).

   Empirical Examples: Researchers discovered keyword identification by
   content providers on platforms ranging from instant messaging
   applications [Senft-2013] to search engines [Rushe-2015] [Cheng-2010]
   [Whittaker-2013] [BBC-2013] [Condliffe-2013].  To demonstrate the
   prevalence of this type of keyword identification, we look to search
   engine censorship.

   Search engine censorship demonstrates keyword identification by
   content providers and can be regional or worldwide.  Implementation
   is occasionally voluntary, but normally it is based on laws and
   regulations of the country a search engine is operating in.  The
   keyword blocklists are most likely maintained by the search engine
   provider.  China is known to require search engine providers to
   "voluntarily" maintain search term blocklists to acquire and keep an
   Internet content provider (ICP) license [Cheng-2010].  It is clear
   these blocklists are maintained by each search engine provider based
   on the slight variations in the intercepted searches [Zhu-2011]
   [Whittaker-2013].  The United Kingdom has been pushing search engines
   to self-censor with the threat of litigation if they do not do it
   themselves: Google and Microsoft have agreed to block more than
   100,000 queries in U.K. to help combat abuse [BBC-2013]
   [Condliffe-2013].  European Union law, as well as US law, requires

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   modification of search engine results in response to either
   copyright, trademark, data protection or defamation concerns

   Depending on the output, search engine keyword identification may be
   difficult or easy to detect.  In some cases specialized or blank
   results provide a trivial enumeration mechanism, but more subtle
   censorship can be difficult to detect.  In February 2015, Microsoft's
   search engine, Bing, was accused of censoring Chinese content outside
   of China [Rushe-2015] because Bing returned different results for
   censored terms in Chinese and English.  However, it is possible that
   censorship of the largest base of Chinese search users, China, biased
   Bing's results so that the more popular results in China (the
   uncensored results) were also more popular for Chinese speakers
   outside of China.

   Disassociation by content distributors from certain categories of
   users has happened for instance in Spain, as a result of the conflict
   between the Catalunyan independence movement and the Spanish legal
   presumption of a unitary state [Lomas-2019].  E-sport event
   organizers have also disassociated themselves from top players who
   expressed political opinions in relation to the 2019 Hong Kong
   protests [Victor-2019].  See also Section 4.3.2.

3.2.4.  Deep Packet Inspection (DPI) Identification

   Deep Packet Inspection has become computationally feasible as a
   censorship mechanism in recent years [Wagner-2009].  Unlike other
   techniques, DPI reassembles network flows to examine the application
   "data" section, as opposed to only headers, and is therefore often
   used for keyword identification.  DPI also differs from other
   identification technologies because it can leverage additional packet
   and flow characteristics, e.g., packet sizes and timings, when
   identifying 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 Indication (SNI)
   sent in the clear for TLS, or metadata about an encrypted flow, e.g.,
   packet sizes, which differ across video and textual flows, to

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   identify traffic.  See Section for more information about
   SNI-based filtration mechanisms.

   Other kinds of information can be inferred by comparing certain
   unencrypted elements exchanged during TLS handshakes to similar data
   points from known sources.  This practice, called TLS fingerprinting,
   allows a probabilistic identification of a party's operating system,
   browser, or application based on a comparison of the specific
   combinations of TLS version, ciphersuites, compression options, etc.
   sent in the ClientHello message to similar signatures found in
   unencrypted traffic [Husak-2016].

   Despite these problems, DPI is the most powerful identification
   method and is widely used in practice.  The Great Firewall of China
   (GFW), the largest censorship system in the world, 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 Examples: Several studies have found evidence of censors
   using DPI for censoring content and tools.  Clayton et al., Crandal
   et al., Anonymous, and Khattak et al., all explored the GFW
   [Crandall-2010] [Clayton-2006] [Anonymous-2014].  Khattak et al. even
   probed the firewall to discover implementation details like how much
   state it stores [Khattak-2013].  The Tor project claims that China,
   Iran, Ethiopia, and others must have used DPI to block the obfs2
   protocol [Wilde-2012].  Malaysia has been accused of using targeted
   DPI, paired with DDoS, to identify and subsequently attack pro-
   opposition material [Wagstaff-2013].  It also seems likely that
   organizations not so worried about blocking content in real-time
   could use DPI to sort and categorically search gathered traffic using
   technologies such as NarusInsight [Hepting-2011].  Server Name Indication

   In encrypted connections using Transport Layer Security (TLS), there
   may be servers that host multiple "virtual servers" at a given
   network address, and the client will need to specify in the
   (unencrypted) Client Hello message which domain name it seeks to
   connect to (so that the server can respond with the appropriate TLS
   certificate) using the Server Name Indication (SNI) TLS extension
   [RFC6066].  Since SNI is often sent in the clear, censors and
   filtering software can use it as a basis for blocking, filtering, or
   impairment by dropping connections to domains that match prohibited
   content (e.g., bad.foo.example may be censored while good.foo.example
   is not) [Shbair-2015].  There are undergoing standardization efforts
   in the TLS Working Group to encrypt SNI [I-D.ietf-tls-sni-encryption]
   [I-D.ietf-tls-esni] and recent research shows promising results in

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   the use of encrypted SNI in the face of SNI-based filtering

   Domain fronting has been one popular way to avoid identification by
   censors [Fifield-2015].  To avoid identification by censors,
   applications using domain fronting put a different domain name in the
   SNI extension than the one encrypted by HTTPS.  The visible SNI would
   indicate an unblocked domain, while the blocked domain remains hidden
   in the encrypted application header.  Some encrypted messaging
   services relied on domain fronting to enable their provision in
   countries employing SNI-based filtering.  These services used the
   cover provided by domains for which blocking at the domain level
   would be undesirable to hide their true domain names.  However, the
   companies holding the most popular domains have since reconfigured
   their software to prevent this practice.  It may be possible to
   achieve similar results using potential future options to encrypt

   Tradeoffs: Some clients do not send the SNI extension (e.g., clients
   that only support versions of SSL and not TLS), rendering this method
   ineffective.  In addition, this technique requires deep packet
   inspection techniques that can be computationally and
   infrastructurally expensive and improper configuration of an SNI-
   based block can result in significant overblocking, e.g., when a
   second-level domain like populardomain.example is inadvertently
   blocked.  In the case of encrypted SNI, pressure to censor may
   transfer to other points of intervention, such as content and
   application providers.

   Empirical Examples: There are many examples of security firms that
   offer SNI-based filtering products [Trustwave-2015] [Sophos-2015]
   [Shbair-2015], and the governments of China, Egypt, Iran, Qatar,
   South Korea, Turkey, Turkmenistan, and the UAE all do widespread SNI
   filtering or blocking [OONI-2018] [OONI-2019] [NA-SK-2019]
   [CitizenLab-2018] [Gatlan-2019] [Chai-2019] [Grover-2019]

3.3.  Transport Layer

3.3.1.  Shallow Packet Inspection and Transport Header Identification

   Of the various shallow packet inspection methods, Transport Header
   Identification is the most pervasive, reliable, and predictable type
   of identification.  Transport headers in TCP/IP or QUIC contain a few
   invaluable pieces of information that must be transparent for traffic
   to be successfully routed: destination and source IP address and
   port.  Destination and Source IP are doubly useful, as not only does
   it allow a censor to block undesirable content via IP blocklisting,

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   but also allows a censor to identify the IP of the user making the
   request and the IP address of the destination being visited, which in
   most cases can be used to infer the domain being visited
   [Patil-2019].  Port is useful for allowlisting certain applications.

   Trade-offs: header identification is popular due to its simplicity,
   availability, and robustness.

   Header identification is trivial to implement, but is difficult to
   implement in backbone or ISP routers at scale, and is therefore
   typically implemented with DPI.  Blocklisting an IP is equivalent to
   installing a /32 route on a router.  However, due to limited flow
   table space, this cannot scale beyond a few thousand IPs at most.  IP
   blocking is also relatively crude.  It often leads 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 web
   content solely on the basis of port.  Another example is HTTPS port
   443, which in addition to handling secure web traffic now also
   carries DNS-over-HTTPS [RFC8484] traffic; this can frustrate
   techniques that rely on cleartext DNS over port 53 for censorship,
   parental control, and other uses [SSAC-109-2020].  Port allowlisting
   is occasionally used, where a censor limits communication to approved
   ports, such as 80 for HTTP traffic and is most effective when used in
   conjunction with other identification mechanisms.  For example, a
   censor could block the default HTTPS port, port 443, thereby forcing
   most users to fall back to HTTP.  An important counter-example is
   that port 25 (SMTP) has long been blocked on residential ISPs'
   networks, ostensibly to reduce the potential for email spam, but also
   prohibiting residential ISP customers to run their own email servers.

3.3.2.  Protocol Identification

   Censors sometimes identify entire protocols to be blocked using a
   variety of traffic characteristics.  For example, Iran impairs the
   performance of HTTPS traffic, a protocol that prevents further
   analysis, to encourage users to switch to HTTP, a protocol that they
   can analyze [Aryan-2012].  A simple protocol identification would be
   to recognize all TCP traffic over port 443 as HTTPS, but more
   sophisticated analysis of the statistical properties of payload data

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   and flow behavior, would be more effective, even when port 443 is not
   used [Hjelmvik-2010] [Sandvine-2014].

   If censors can detect circumvention tools, they can block them, so
   censors like China are extremely interested in identifying the
   protocols for censorship circumvention tools.  In recent years, this
   has devolved into an arms race between censors and circumvention tool
   developers.  As part of this arms race, China developed an extremely
   effective protocol identification technique that researchers call
   active probing or active scanning.

   In active probing, the censor determines whether hosts are running a
   circumvention protocol by trying to initiate communication using the
   circumvention protocol.  If the host and the censor successfully
   negotiate a connection, then the censor conclusively knows that host
   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 over-blocking
   problems when used with popular protocols.  These methods are
   expensive, both computationally and financially, due to the use of
   statistical analysis, and can be ineffective due to their imprecise
   nature.  Moreover, censorship circumvention groups like the Tor
   Project have developed "pluggable transports" which seek to make the
   traffic of censorship circumvention tools appear indistinguishable
   from other kinds of traffic [Tor-2020].

   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

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4.  Technical Interference

4.1.  Application Layer

4.1.1.  DNS Interference

   There are a variety of mechanisms that censors can use to block or
   filter access to content by altering responses from the DNS
   [AFNIC-2013] [ICANN-SSAC-2012], including blocking the response,
   replying with an error message, or responding with an incorrect
   address.  Note that there are now encrypted transports for DNS
   queries in DNS-over-HTTPS [RFC8484] and DNS-over-TLS [RFC7858] that
   can mitigate interference with DNS queries between the stub and the

   "DNS mangling" is a network-level technique where an incorrect IP
   address is returned in response to a DNS query to a censored
   destination.  An example of this is what some Chinese networks do (we
   are not aware of any other wide-scale uses of mangling).  On those
   Chinese networks, every DNS request in transit is examined
   (presumably by network inspection technologies such as DPI) and, if
   it matches a censored domain, a false response is injected.  End
   users can see this technique in action by simply sending DNS requests
   to any unused IP address in China (see example below).  If it is not
   a censored name, there will be no response.  If it is censored, a
   forged response will be returned.  For example, using the command-
   line dig utility to query an unused IP address in China of
   for the name "www.uncensored.example" compared with
   "www.censored.example" (censored at the time of writing), we get a
   forged IP address "" as a response:

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

   % dig +short +nodnssec @ A www.censored.example

   There are also cases of what is colloquially called "DNS lying",
   where a censor mandates that the DNS responses provided - by an
   operator of a recursive resolver such as an Internet access provider
   - be different than what authoritative resolvers would provide

   DNS cache poisoning refers to a mechanism where a censor interferes
   with the response sent by an authoritative DNS resolver to a
   recursive resolver by responding more quickly than the authoritative
   resolver can respond with an alternative IP address [Halley-2008].
   Cache poisoning occurs after the requested site's name servers

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   resolve the request and attempt to forward the true IP back to the
   requesting device; on the return route the resolved IP is recursively
   cached by each DNS server that initially forwarded the request.
   During this caching process if an undesirable keyword is recognized,
   the resolved IP is "poisoned" and an alternative IP (or NXDOMAIN
   error) is returned more quickly than the upstream resolver can
   respond, causing a forged IP address to be cached (and potentially
   recursively so).  The alternative IPs usually direct to a nonsense
   domain or a warning page.  Alternatively, Iranian censorship appears
   to prevent the communication en-route, preventing a response from
   ever being sent [Aryan-2012].

   Trade-offs: These forms of DNS interference require the censor to
   force a user to traverse a controlled DNS hierarchy (or intervening
   network on which the censor serves as a Active Pervasive Attacker
   [RFC7624] to rewrite DNS responses) for the mechanism to be
   effective.  It can be circumvented by using alternative DNS resolvers
   (such as any of the public DNS resolvers) that may fall outside of
   the jurisdictional control of the censor, or Virtual Private Network
   (VPN) technology.  DNS mangling and cache poisoning also imply
   returning an incorrect IP to those attempting to resolve a domain
   name, but in some cases the destination may be technically
   accessible; over HTTP, for example, the user may have another method
   of obtaining the IP address of the desired site and may be able to
   access it if the site is configured to be the default server
   listening at this IP address.  Target blocking has also been a
   problem, as occasionally users outside of the censors region will be
   directed through DNS servers or DNS-rewriting network equipment
   controlled by a censor, causing the request to fail.  The ease of
   circumvention paired with the large risk of content blocking and
   target blocking make DNS interference a partial, difficult, and less
   than ideal censorship mechanism.  Additionally, the above mechanisms
   rely on DNSSEC not being deployed or DNSSEC validation not being
   active on the client or recursive resolver (neither of which are hard
   to imagine given limited deployment of DNSSEC and limited client
   support for DNSSEC validation).

   Empirical Examples: DNS interference, when properly implemented, is
   easy to identify based on the shortcomings identified above.  Turkey
   relied on DNS interference for its country-wide block of websites
   such Twitter and YouTube for almost week in March of 2014 but the
   ease of circumvention resulted in an increase in the popularity of
   Twitter until Turkish ISPs implementing an IP blocklist to achieve
   the governmental mandate [Zmijewski-2014].  Ultimately, Turkish ISPs
   started hijacking all requests to Google and Level 3's international
   DNS resolvers [Zmijewski-2014].  DNS interference, when incorrectly
   implemented, has resulted in some of the largest "censorship
   disasters".  In January 2014, China started directing all requests

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   passing through the Great Fire Wall to a single domain,
   dongtaiwang.com, due to an improperly configured DNS poisoning
   attempt; this incident is thought to be the largest Internet-service
   outage in history [AFP-2014] [Anon-SIGCOMM12].  Countries such as
   China, Iran, Turkey, and the United States have discussed blocking
   entire TLDs as well, but only Iran has acted by blocking all Israeli
   (.il) domains [Albert-2011].  DNS-blocking is commonly deployed in
   European countries to deal with undesirable content, such as child
   abuse content (Norway, United Kingdom, Belgium, Denmark, Finland,
   France, Germany, Ireland, Italy, Malta, the Netherlands, Poland,
   Spain and Sweden [Wright-2013] [Eneman-2010]), online gambling
   (Belgium, Bulgaria, Czech Republic, Cyprus, Denmark, Estonia, France,
   Greece, Hungary, Italy, Latvia, Lithuania, Poland, Portugal, Romania,
   Slovakia, Slovenia, Spain (see Section 6.3.2 of: [EC-gambling-2012],
   [EC-gambling-2019])), copyright infringement (all European Economic
   Area countries), hate-speech and extremism (France [Hertel-2015]) and
   terrorism content (France [Hertel-2015]).  Many European DNS
   filtering systems function as described in section 6.2.

4.2.  Transport Layer

4.2.1.  Performance Degradation

   While other interference techniques outlined in this section mostly
   focus on blocking or preventing access to content, it can be an
   effective censorship strategy in some cases to not entirely block
   access to a given destination, or service but instead degrade the
   performance of the relevant network connection.  The resulting user
   experience for a site or service under performance degradation can be
   so bad that users opt to use a different site, service, or method of
   communication, or may not engage in communication at all if there are
   no alternatives.  Traffic shaping techniques that rate-limit the
   bandwidth available to certain types of traffic is one example of a
   performance degradation.

   Trade offs: While implementing a performance degradation will not
   always eliminate the ability of people to access a desire resource,
   it may force them to use other means of communication where
   censorship (or surveillance) is more easily accomplished.

   Empirical Examples: Iran has been known to shape the bandwidth
   available to HTTPS traffic to encourage unencrypted HTTP traffic

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4.2.2.  Packet Dropping

   Packet dropping is a simple mechanism to prevent undesirable traffic.
   The censor identifies undesirable traffic and chooses to not properly
   forward any packets it sees associated with the traversing
   undesirable traffic instead of following a normal routing protocol.
   This can be paired with any of the previously described mechanisms so
   long as the censor knows the user must route traffic through a
   controlled router.

   Trade offs: Packet Dropping is most successful when every traversing
   packet has transparent information linked to undesirable content,
   such as a Destination IP.  One downside Packet Dropping suffers from
   is the necessity of blocking all content from otherwise allowable IPs
   based on a single subversive sub-domain; blogging services and github
   repositories are good examples.  China famously dropped all github
   packets for three days based on a single repository hosting
   undesirable content [Anonymous-2013].  The need to inspect every
   traversing packet in close to real time also makes Packet Dropping
   somewhat challenging from a QoS perspective.

   Empirical Examples: Packet Dropping is a very common form of
   technical interference and lends itself to accurate detection given
   the unique nature of the time-out requests it leaves in its wake.
   The Great Firewall of China has been observed using packet dropping
   as one of its primary mechanisms of technical censorship
   [Ensafi-2013].  Iran has also used Packet Dropping as the mechanisms
   for throttling SSH [Aryan-2012].  These are but two examples of a
   ubiquitous censorship practice.

4.2.3.  RST Packet Injection

   Packet injection, generally, refers to a man-in-the-middle (MITM)
   network interference technique that spoofs packets in an established
   traffic stream.  RST packets are normally used to let one side of TCP
   connection know the other side has stopped sending information, and
   thus the receiver should close the connection.  RST Packet Injection
   is a specific type of packet injection attack that is used to
   interrupt an established stream by sending RST packets to both sides
   of a TCP connection; as each receiver thinks the other has dropped
   the connection, the session is terminated.  QUIC is not vulnerable to
   these types of injection attacks (See [I-D.ietf-quic-transport] for
   more details).

   Trade-offs: Although ineffective against non-TCP protocols (QUIC,
   IPSec), RST Packet Injection has a few advantages that make it
   extremely popular as a censorship technique.  RST Packet Injection is
   an out-of-band interference mechanism, allowing the avoidance of the

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   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.  Recent
   research shows that a TCP RST packet injection attack can even work
   in the case of an off-path attacker [Cao-2016].

   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].

4.3.  Multi-layer and Non-layer

4.3.1.  Distributed Denial of Service (DDoS)

   Distributed Denial of Service attacks are a common attack mechanism
   used by "hacktivists" and malicious hackers, but censors have used
   DDoS in the past for a variety of reasons.  There is a huge variety

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   of DDoS attacks [Wikip-DoS], but on a high level two possible impacts
   tend to occur; a flood attack results in the service being unusable
   while resources are being spent to flood the service, a crash attack
   aims to crash the service so resources can be reallocated elsewhere
   without "releasing" the service.

   Trade-offs: DDoS is an appealing mechanism when a censor would like
   to prevent all access to undesirable content, instead of only access
   in their region for a limited period of time, but this is really the
   only uniquely beneficial feature for DDoS as a censorship technique.
   The resources required to carry out a successful DDoS against major
   targets are computationally expensive, usually requiring renting or
   owning a malicious distributed platform such as a botnet, and
   imprecise.  DDoS is an incredibly crude censorship technique, and
   appears to largely be used as a timely, easy-to-access mechanism for
   blocking undesirable content for a limited period of time.

   Empirical Examples: In 2012 the U.K.'s GCHQ used DDoS to temporarily
   shutdown IRC chat rooms frequented by members of Anonymous using the
   Syn Flood DDoS method; Syn Flood exploits the handshake used by TCP
   to overload the victim server with so many requests that legitimate
   traffic becomes slow or impossible [Schone-2014] [CERT-2000].
   Dissenting opinion websites are frequently victims of DDoS around
   politically sensitive events in Burma [Villeneuve-2011].  Controlling
   parties in Russia [Kravtsova-2012], Zimbabwe [Orion-2013], and
   Malaysia [Muncaster-2013] have been accused of using DDoS to
   interrupt opposition support and access during elections.  In 2015,
   China launched a DDoS attack using a true MITM system collocated with
   the Great Firewall, dubbed "Great Cannon", that was able to inject
   JavaScript code into web visits to a Chinese search engine that
   commandeered those user agents to send DDoS traffic to various sites

4.3.2.  Network Disconnection or Adversarial Route Announcement

   While it is perhaps the crudest of all censorship techniques, there
   is no more effective way of making sure undesirable information isn't
   allowed to propagate on the web than by shutting off the network.
   The network can be logically cut off in a region when a censoring
   body withdraws all of the Boarder Gateway Protocol (BGP) prefixes
   routing through the censor's country.

   Trade-offs: The impact to a network disconnection in a region is huge
   and absolute; the censor pays for absolute control over digital
   information with all the benefits the Internet brings; this is never
   a long-term solution for any rational censor and is normally only
   used as a last resort in times of substantial unrest.

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   Empirical Examples: Network Disconnections tend to only happen in
   times of substantial unrest, largely due to the huge social,
   political, and economic impact such a move has.  One of the first,
   highly covered occurrences was with the Junta in Myanmar employing
   Network Disconnection to help Junta forces quash a rebellion in 2007
   [Dobie-2007].  China disconnected the network in the Xinjiang region
   during unrest in 2009 in an effort to prevent the protests from
   spreading to other regions [Heacock-2009].  The Arab Spring saw the
   the most frequent usage of Network Disconnection, with events in
   Egypt and Libya in 2011 [Cowie-2011] [Cowie-2011b], and Syria in 2012
   [Thomson-2012].  Russia has indicated that it will attempt to
   disconnect all Russian networks from the global internet in April
   2019 as part of a test of the nation's network independence.  Reports
   also indicate that, as part of the test disconnect, Russian
   telecommunications firms must now route all traffic to state-operated
   monitoring points [Cimpanu-2019].  India was the country that saw the
   largest number of internet shutdowns per year in 2016 and 2017

5.  Non-Technical Prescription

   As the name implies, sometimes manpower is the easiest way to figure
   out which content to block.  Manual Filtering differs from the common
   tactic of building up blocklists in that it doesn't necessarily
   target a specific IP or DNS, but instead removes or flags content.
   Given the imprecise nature of automatic filtering, manually sorting
   through content and flagging dissenting websites, blogs, articles and
   other media for filtration can be an effective technique.  This
   filtration can occur on the Backbone/ISP level - China's army of
   monitors is a good example [BBC-2013b] - but more commonly manual
   filtering occurs on an institutional level.  Internet Content
   Providers such as Google or Weibo, require a business license to
   operate in China.  One of the prerequisites for a business license is
   an agreement to sign a "voluntary pledge" known as the "Public Pledge
   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 the effects of surveillance (e.g., on the
   proverbial prisoners in Bentham's Panopticon [Bentham-1791]),
   cultural manipulation, intelligence gathering, and offline

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   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.
   Moreover, regimes can manipulate public opinion in ways that result
   in self-censorship [Ellul-1973].  Self-censorship is difficult to
   document, as when it is implemented effectively the only noticeable
   evidence is a lack of undesirable content; instead one must look at
   the tools and techniques used by censors to encourage self-
   censorship.  Controlling information relies heavily on surveillance -
   e.g., by forcing all users to connect through an intranet, such as in
   North Korea - and traditional censorship techniques.  Intimidation is
   often achieved through allowing Internet users to post "whatever they
   want," but arresting or otherwise putting pressure on those who post
   about dissenting views.  This technique is incredibly common
   [Calamur-2013] [AP-2012] [Hopkins-2011] [Guardian-2014]
   [Johnson-2010].  A good example of swaying public thought is China's
   "50-Cent Party," reported to be composed of somewhere between 20,000
   [Bristow-2013] and 300,000 [Fareed-2008] contributors who are paid to
   "guide public thought" on local and regional issues as directed by
   the Ministry of Culture.  Creating apathy can be a side-effect of
   successfully controlling information over time and is ideal for a
   censorship regime [Gao-2014].

6.2.  Server Takedown

   Servers must have a physical location somewhere in the world.  If
   undesirable content is hosted in the censoring country the servers
   can be physically seized or the hosting provider can be required to
   prevent access [Anderson-2011].

6.3.  Notice and Takedown

   In many countries, legal mechanisms exist where an individual or
   other content provider can issue a legal request to a content host
   that requires the host to take down content.  Examples include the
   systems employed by companies like Google to comply with "Right to be
   Forgotten" policies in the European Union [Google-RTBF], intermediary
   liability rules for electronic platform providers [EC-2012], or the
   copyright-oriented notice and takedown regime of the United States
   Digital Millennium Copyright Act (DMCA) Section 512 [DMLP-512].

7.  Contributors

   This document benefited from discussions with and input from David
   Belson, Stephane Bortzmeyer, Vinicius Fortuna, Gurshabad Grover,

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   Andrew McConachie, Martin Nilsson, Michael Richardson, Patrick Vacek
   and Chris Wood.

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, <https://opennet.net/blog/2011/06/dns-tampering-and-

              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, <https://torrentfreak.com/how-to-

              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, <http://www.bbc.com/news/uk-24980765>.

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

              Bentham, J., "Panopticon Or the Inspection House", 1791,

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

              Boyle, J., "Foucault in Cyberspace: Surveillance,
              Sovereignty, and Hardwired Censors", 1997,

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

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

              Cao, Y., Qian, Z., Wang, Z., Dao, T., Krishnamurthy, S.,
              and L. Marvel, "Off-Path TCP Exploits: Global Rate Limit
              Considered Dangerous", 2016,

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

              Chai, Z., Ghafari, A., and A. Houmansadr, "On the
              Importance of Encrypted-SNI (ESNI) to Censorship
              Circumvention", 2019,

              Cheng, J., "Google stops Hong Kong auto-redirect as China
              plays hardball", 2010, <http://arstechnica.com/tech-

              Cimpanu, C., "Russia to disconnect from the internet as
              part of a planned test", 2019,

              Marczak, B., Dalek, J., McKune, S., Senft, A., Scott-
              Railton, J., and R. Deibert, "Bad Traffic: Sandvine's
              PacketLogic Devices Used to Deploy Government Spyware in
              Turkey and Redirect Egyptian Users to Affiliate Ads?",
              2018, <https://citizenlab.ca/2018/03/bad-traffic-

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

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              Condliffe, J., "Google Announces Massive New Restrictions
              on Child Abuse Search Terms", 2013, <http://gizmodo.com/

              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,

              Dada, T. and P. Micek, "Launching STOP: the #KeepItOn
              internet shutdown tracker", 2017,

              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, <http://citeseerx.ist.psu.edu/viewdoc/

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

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

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   [EC-2012]  European Commission, "Summary of the results of the Public
              Consultation on the future of electronic commerce in the
              Internal Market and the implementation of the Directive on
              electronic commerce (2000/31/EC)", 2012,

              European Commission, "Online gambling in the Internal
              Market", 2012, <https://eur-lex.europa.eu/legal-

              European Commission, "Evaluation of regulatory tools for
              enforcing online gambling rules and channeling demand
              towards controlled offers", 2019,

              Ellul, J., "Propaganda: The Formation of Men's Attitudes",
              1973, <https://www.penguinrandomhouse.com/books/46234/

              Eneman, M., "ISPs filtering of child abusive material: A
              critical reflection of its effectiveness", 2010,

              Ensafi, R., "Detecting Intentional Packet Drops on the
              Internet via TCP/IP Side Channels", 2013,

              Fareed, M., "China joins a turf war", 2008,

              Fifield, D., Lan, C., Hynes, R., Wegmann, P., and V.
              Paxson, "Blocking-resistant communication through domain
              fronting", 2015,

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

              Gatlan, S., "South Korea is Censoring the Internet by
              Snooping on SNI Traffic", 2019,

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

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

              Grover, G., Singh, K., and E. Hickok, "Reliance Jio is
              using SNI inspection to block websites", 2019,

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

              Haute Autorite pour la Diffusion des oeuvres et la
              Protection des Droits sur Internet, "Presentation", 2020,

              Halley, B., "How DNS cache poisoning works", 2014,

Hall, et al.            Expires November 19, 2020              [Page 27]

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              Heacock, R., "China Shuts Down Internet in Xinjiang Region
              After Riots", 2009, <https://opennet.net/blog/2009/07/

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

              Hertel, O., "Comment les autorites peuvent bloquer un site
              Internet", 2015, <https://www.sciencesetavenir.fr/high-

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

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

              Husak, M., Cermak, M., Jirsik, T., and P. Celeda, "HTTPS
              traffic analysis and client identification using passive
              SSL/TLS fingerprinting", 2016,

              Iyengar, J. and M. Thomson, "QUIC: A UDP-Based Multiplexed
              and Secure Transport", draft-ietf-quic-transport-27 (work
              in progress), February 2020.

              Rescorla, E., Oku, K., Sullivan, N., and C. Wood,
              "Encrypted Server Name Indication for TLS 1.3", draft-
              ietf-tls-esni-06 (work in progress), March 2020.

              Huitema, C. and E. Rescorla, "Issues and Requirements for
              SNI Encryption in TLS", draft-ietf-tls-sni-encryption-09
              (work in progress), October 2019.

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              ICANN Security and Stability Advisory Committee (SSAC),
              "SAC 056: SSAC Advisory on Impacts of Content Blocking via
              the Domain Name System", 2012,

              Johnson, L., "Torture feared in arrest of Iraqi blogger",
              2011, <http://seattlepostglobe.org/2010/02/05/torture-

              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

              Knight, W., "Iranian net censorship powered by US
              technology", 2005, <https://www.newscientist.com/article/

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              Government is Taking Domain Names Without Prior Notice",
              2013, <http://dx.doi.org/doi:10.15779/Z384Q3M>.

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              Election", 2012,

              Leyba, K., Edwards, B., Freeman, C., Crandall, J., and S.
              Forrest, "Borders and Gateways: Measuring and Analyzing
              National AS Chokepoints", 2019,

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              Lomas, N., "Github removes Tsunami Democratic's APK after
              a takedown order from Spain", 2019,

              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,

              Morgus, R., Sherman, J., and S. Nam, "Analysis: South
              Korea's New Tool for Filtering Illegal Internet Content",
              2019, <https://www.newamerica.org/cybersecurity-

              Nabi, Z., "The Anatomy of Web Censorship in Pakistan",
              2013, <http://0b4af6cdc2f0c5998459-c0245c5c937c5dedcca3f17

              n3t2.3c, "TCP-RST Injection", 2011,

              Evdokimov, L., "Iran Protests: DPI blocking of Instagram
              (Part 2)", 2018,

              Singh, S., Filasto, A., and M. Xynou, "China is now
              blocking all language editions of Wikipedia", 2019,

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

              Patil, S. and N. Borisov, "What Can You Learn from an
              IP?", 2019, <https://irtf.org/anrw/2019/

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

              Reda, J., "New EU law prescribes website blocking in the
              name of 'consumer protection'", 2017,

   [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,

   [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, <https://www.rfc-editor.org/info/rfc7754>.

   [RFC7858]  Hu, Z., Zhu, L., Heidemann, J., Mankin, A., Wessels, D.,
              and P. Hoffman, "Specification for DNS over Transport
              Layer Security (TLS)", RFC 7858, DOI 10.17487/RFC7858, May
              2016, <https://www.rfc-editor.org/info/rfc7858>.

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   [RFC8484]  Hoffman, P. and P. McManus, "DNS Queries over HTTPS
              (DoH)", RFC 8484, DOI 10.17487/RFC8484, October 2018,

              Reporters Sans Frontieres, "Technical ways to get around
              censorship", 2005, <http://archives.rsf.org/print-

              Rushe, D., "Bing censoring Chinese language search results
              for users in the US", 2013,

              Sandvine, "Technology Showcase on Traffic Classification:
              Why Measurements and Freeform Policy Matter", 2014,

              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, <http://www.nbcnews.com/feature/edward-snowden-

              Senft, A., "Asia Chats: Analyzing Information Controls and
              Privacy in Asian Messaging Applications", 2013,

              Shbair, W., Cholez, T., Goichot, A., and I. Chrisment,
              "Efficiently Bypassing SNI-based HTTPS Filtering", 2015,

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              Singh, K., Grover, G., and V. Bansal, "How India Censors
              the Web", 2019, <https://arxiv.org/abs/1912.08590>.

              Sophos, "Understanding Sophos Web Filtering", 2015,

              ICANN Security and Stability Advisory Committee, "SAC109:
              The Implications of DNS over HTTPS and DNS over TLS",
              2020, <https://www.icann.org/en/system/files/files/sac-

              Tang, C., "In-depth analysis of the Great Firewall of
              China", 2016,

              Thomson, I., "Syria Cuts off Internet and Mobile
              Communication", 2012,

              The Tor Project, "Tor: Pluggable Transports", 2020,

              Trustwave, "Filter: SNI extension feature and HTTPS
              blocking", 2015,

              Tschantz, M., Afroz, S., Anonymous, A., and V. Paxson,
              "SoK: Towards Grounding Censorship Circumvention in
              Empiricism", 2016,

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              Verkamp, J. and M. Gupta, "Inferring Mechanics of Web
              Censorship Around the World", 2012,

              Victor, D., "Blizzard Sets Off Backlash for Penalizing
              Hearthstone Gamer in Hong Kong", 2019,

              Villeneuve, N., "Open Access: Chapter 8, Control and
              Resistance, Attacks on Burmese Opposition Media", 2011,

              VonLohmann, F., "FCC Rules Against Comcast for BitTorrent
              Blocking", 2008, <https://www.eff.org/deeplinks/2008/08/

              Wagner, B., "Deep Packet Inspection and Internet
              Censorship: International Convergence on an 'Integrated
              Technology of Control'", 2009,

              Wagstaff, J., "In Malaysia, online election battles take a
              nasty turn", 2013,

              Weaver, N., Sommer, R., and V. Paxson, "Detecting Forged
              TCP Packets", 2009, <http://www.icir.org/vern/papers/

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

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              Wikipedia, "Denial of Service Attacks", 2016,

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

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

              Wikipedia contributors, "Censorship", 2020,

              Wright, J. and Y. Breindl, "Internet filtering trends in
              liberal democracies: French and German regulatory
              debates", 2013,

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

              Zmijewski, E., "Turkish Internet Censorship Takes a New
              Turn", 2014, <http://www.renesys.com/2014/03/turkish-

Authors' Addresses

   Joseph Lorenzo Hall
   Internet Society

   Email: hall@isoc.org

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   Michael D. Aaron
   CU Boulder

   Email: michael.drew.aaron@gmail.com

   Stan Adams

   Email: sadams@cdt.org

   Amelia Andersdotter

   Email: amelia.ietf@andersdotter.cc

   Ben Jones

   Email: bj6@cs.princeton.edu

   Nick Feamster
   U Chicago

   Email: feamster@uchicago.edu

Hall, et al.            Expires November 19, 2020              [Page 36]

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