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A Survey of Worldwide Censorship Techniques
draft-irtf-pearg-censorship-09

Document Type Active Internet-Draft (pearg RG)
Authors Joseph Lorenzo Hall , Michael D. Aaron , Amelia Andersdotter , Ben Jones , Nick Feamster , Mallory Knodel
Last updated 2023-01-12 (Latest revision 2023-01-10)
Replaces draft-hall-censorship-tech
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draft-irtf-pearg-censorship-09
pearg                                                         J. L. Hall
Internet-Draft                                          Internet Society
Intended status: Informational                               M. D. Aaron
Expires: 14 July 2023                                         CU Boulder
                                                         A. Andersdotter
                                                                        
                                                                B. Jones
                                                                        
                                                             N. Feamster
                                                               U Chicago
                                                               M. Knodel
                                       Center for Democracy & Technology
                                                         10 January 2023

              A Survey of Worldwide Censorship Techniques
                     draft-irtf-pearg-censorship-09

Abstract

   This document describes technical mechanisms employed in network
   censorship that 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.  This document
   is a product of the Privacy Enhancement and Assessment Research Group
   (PEARG) in the IRTF.

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 14 July 2023.

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Copyright Notice

   Copyright (c) 2023 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 Revised BSD License text as
   described in Section 4.e of the Trust Legal Provisions and are
   provided without warranty as described in the Revised BSD License.

Table of Contents

   1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   3
   2.  Terminology . . . . . . . . . . . . . . . . . . . . . . . . .   3
   3.  Technical Prescription  . . . . . . . . . . . . . . . . . . .   4
   4.  Technical Identification  . . . . . . . . . . . . . . . . . .   5
     4.1.  Points of Control . . . . . . . . . . . . . . . . . . . .   5
     4.2.  Application Layer . . . . . . . . . . . . . . . . . . . .   7
       4.2.1.  HTTP Request Header Identification  . . . . . . . . .   7
       4.2.2.  HTTP Response Header Identification . . . . . . . . .   8
       4.2.3.  Transport Layer Security (TLS)  . . . . . . . . . . .   9
       4.2.4.  Instrumenting Content Distributors  . . . . . . . . .  11
       4.2.5.  DPI Identification  . . . . . . . . . . . . . . . . .  13
     4.3.  Transport Layer . . . . . . . . . . . . . . . . . . . . .  15
       4.3.1.  Shallow Packet Inspection and Transport Header
               Identification  . . . . . . . . . . . . . . . . . . .  15
       4.3.2.  Protocol Identification . . . . . . . . . . . . . . .  16
     4.4.  Residual Censorship . . . . . . . . . . . . . . . . . . .  17
   5.  Technical Interference  . . . . . . . . . . . . . . . . . . .  18
     5.1.  Application Layer . . . . . . . . . . . . . . . . . . . .  18
       5.1.1.  DNS Interference  . . . . . . . . . . . . . . . . . .  18
     5.2.  Transport Layer . . . . . . . . . . . . . . . . . . . . .  21
       5.2.1.  Performance Degradation . . . . . . . . . . . . . . .  21
       5.2.2.  Packet Dropping . . . . . . . . . . . . . . . . . . .  21
       5.2.3.  RST Packet Injection  . . . . . . . . . . . . . . . .  22
     5.3.  Routing Layer . . . . . . . . . . . . . . . . . . . . . .  23
       5.3.1.  Network Disconnection . . . . . . . . . . . . . . . .  24
       5.3.2.  Adversarial Route Announcement  . . . . . . . . . . .  24
     5.4.  Multi-layer and Non-layer . . . . . . . . . . . . . . . .  25
       5.4.1.  Distributed Denial of Service (DDoS)  . . . . . . . .  25
       5.4.2.  Censorship in Depth . . . . . . . . . . . . . . . . .  26
   6.  Non-Technical Interference  . . . . . . . . . . . . . . . . .  27
     6.1.  Manual Filtering  . . . . . . . . . . . . . . . . . . . .  27
     6.2.  Self-Censorship . . . . . . . . . . . . . . . . . . . . .  27

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     6.3.  Server Takedown . . . . . . . . . . . . . . . . . . . . .  27
     6.4.  Notice and Takedown . . . . . . . . . . . . . . . . . . .  28
     6.5.  Domain-Name Seizures  . . . . . . . . . . . . . . . . . .  28
   7.  Future work . . . . . . . . . . . . . . . . . . . . . . . . .  28
   8.  Contributors  . . . . . . . . . . . . . . . . . . . . . . . .  29
   9.  Informative References  . . . . . . . . . . . . . . . . . . .  29
   Authors' Addresses  . . . . . . . . . . . . . . . . . . . . . . .  45

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.

   Censorship circumvention also impacts the cost of implementation of a
   censorship measure and we include mentions of tradeoffs in relation
   to such costs in conjunction with each technical method identified
   below.

   This document has seen extensive discussion and review in the IRTF
   Privacy Enhancement and Assessment Research Group (PEARG) and
   represents the consensus of that group.  It is not an IETF product
   and is not a standard.

2.  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 censor, e.g., classifying pornographic websites as
   undesirable.  Identification is the process by which censors classify
   specific traffic or traffic identifiers to be blocked or impaired,
   e.g., deciding that webpages containing "sex" in an HTTP Header or
   that accept traffic through the URL www.sex.example are likely to be

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   undesirable.  Interference is the process by which censors intercede
   in communication and prevents access to censored materials by
   blocking access or impairing the connection, e.g., implementing a
   technical solution capable of identifying HTTP headers or URLs and
   ensuring they are rendered wholly or partially inaccessible.

3.  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, databases of image hashes [ekr-2021], 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].  Indeed,
   web crawling and machine learning techniques are an active research
   idea in the effort to identify content deemed as morally or
   commercially harmful to companies or consumers in some jurisdictions
   [SIDN2020].

   There are typically a few types of blocklist elements: Keyword,
   domain name, protocol, or Internet Protocol (IP) address.  Keyword
   and domain name blocking take place at the application level, e.g.,
   HTTP; protocol blocking often occurs using deep packet inspection to
   identify a forbidden protocol; IP blocking tends to take place using
   IP addresses in IPv4/IPv6 headers.  Some censors also use the
   presence of certain keywords to enable more aggressive blocklists
   [Rambert-2021] or to be more permissive with content [Knockel-2021].

   The mechanisms for building up these blocklists vary.  Censors can
   purchase from private industry "content control" software, 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 content.

   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].

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   Content-layer filtering of images and video require institutions or
   organizations to store hashes of images or videos to be blocked in
   databases, which can then be compared, with some degree of tolerance,
   to content that is sent, received or stored using centralized,
   content applications and services [ekr-2021].

4.  Technical Identification

4.1.  Points of Control

   Internet censorship takes place in all parts of the network topology.
   It may be implemented in the network itself (e.g. local loop or
   backhaul), on the services side of communication (e.g. web hosts,
   cloud providers or content delivery networks), in the ancillary
   services eco-system (e.g. domain name system or certificate
   authorities) or on the end-client side (e.g. in an end-user device
   such as a smartphone, laptop or desktop or software executed on such
   devices).  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.

   *  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].

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

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   *  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.

   *  Content Distribution Network (CDN): 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
      repositories allow for easier interference.

   *  Certificate Authorities (CAs) for Public-Key Infrastructures
      (PKIs): Authorities that issue cryptographically secured resources
      can be a significant point of control.  CAs 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.  CAs may also be forced to
      revoke certificates.  This may lead to adversarial traffic routing
      or TLS interception being allowed, or an otherwise rightful origin
      or destination point of traffic flows being unable to communicate
      in a secure way.

   *  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.

   *  Content sites: On the service side of communications lie many
      platforms that publish user-generated content require terms of
      service compliance with all content and user accounts in order to
      avoid intermediary liability for the web hosts.  In aggregate
      these policies, actions and remedies are known as content
      moderation.  Content moderation happens above the services or
      application layer, but these mechanisms are built to filter, sort
      and block content and users thus making them available to censors
      through direct pressure on the private entity.

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

   At all levels of the network hierarchy, the filtration mechanisms
   used to censor undesirable traffic are essentially the same: a censor
   either directly identifies undesirable content using the identifiers
   described below and then uses a blocking or shaping mechanism such as
   the ones exemplified below 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 4.2.1 and
   Section 4.2.2).  For example, a subversive image might make it past a
   keyword filter.  However, if later the image is deemed undesirable, a
   censor may then blocklist the provider site's IP address.

4.2.  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.

4.2.1.  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 4.3.1) 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

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   are a concern.  HTTPS will encrypt the relevant request and response
   fields, so pairing with transport identification (see Section 4.3.1)
   is necessary for HTTPS filtering.  However, some countermeasures 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.

   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 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] [Jones-2014].

4.2.2.  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 4.2.4), it is likely that most censors rely on
   keyword filtering over TCP streams instead of HTTP response
   filtering.

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4.2.3.  Transport Layer Security (TLS)

   Similar to HTTP, censors have deployed a variety of techniques
   towards censoring Transport Layer Security (TLS) (and by extension
   HTTPS).  Most of these techniques relate to the Server Name
   Indication (SNI) field, including censoring SNI, Encrypted SNI, or
   omitted SNI.  Censors can also censor HTTPS content via server
   certificates.  Note that TLS 1.3 acts as a security component of
   QUIC.

4.2.3.1.  Server Name Indication (SNI)

   In encrypted connections using TLS, there may be servers that host
   multiple "virtual servers" at a given network address, and the client
   will need to specify in the 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].  The Client Hello message is unencrypted for
   TCP-based TLS.  When using QUIC, the Client Hello message is
   encrypted but its confidentiality is not effectively protected
   because the initial encryption keys are derived using a value that is
   visible on the wire.  Since SNI is often sent in the clear (as are
   the cert fields sent in response), censors and filtering software can
   use it (and response cert fields) 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 the use of encrypted SNI in the face of
   SNI-based filtering [Chai-2019] in some countries.

   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 in the Host: header, which is protected 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 SNI.

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   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 (see Section 4.2.3.3).  In addition, this technique
   requires deep packet inspection (DPI) techniques that can be
   computationally and infrastructurally expensive, especially when
   applied to QUIC where DPI requires key extraction and decryption of
   the Client Hello in order to read the SNI.  Improper configuration of
   an SNI-based block can result in significant overblocking, e.g., when
   a second-level domain like populardomain.example is inadvertently
   blocked.  In the case of encrypted SNI, pressure to censor may
   transfer to other points of intervention, such as content and
   application providers.

   Empirical Examples: There are many examples of security firms that
   offer SNI-based filtering products [Trustwave-2015] [Sophos-2015]
   [Shbair-2015], and the governments of China, Egypt, Iran, Qatar,
   South Korea, Turkey, Turkmenistan, and the UAE all do widespread SNI
   filtering or blocking [OONI-2018] [OONI-2019] [NA-SK-2019]
   [CitizenLab-2018] [Gatlan-2019] [Chai-2019] [Grover-2019]
   [Singh-2019].  SNI blocking against QUIC traffic has been first
   observed in Russia in March 2022 [Elmenhorst-2022].

4.2.3.2.  Encrypted SNI (ESNI)

   With the data leakage present with the SNI field, a natural response
   is to encrypt it, which is forthcoming in TLS 1.3 with Encrypted
   Client Hello (ECH).  Prior to ECH, the Encrypted SNI (ESNI) extension
   is available to prevent the data leakage caused by SNI, which
   encrypts only the SNI field.  Unfortunately, censors can target
   connections that use the ESNI extension specifically for censorship.
   This guarantees overblocking for the censor, but can be worth the
   cost if ESNI is not yet widely deployed within the country.
   Encrypted Client Hello (ECH) is the emerging standard for protecting
   the entire TLS Client Hello, but it is not yet widely deployed.

   Tradeoffs: The cost to censoring Encrypted SNI (ESNI) is
   significantly higher than SNI to a censor, as the censor can no
   longer target censorship to specific domains and guarantees over-
   blocking.  In these cases, the censor uses the over-blocking to
   discourage the use of ESNI entirely.

   Empirical Examples: In 2020, China began censoring all uses of
   Encrypted ESNI (ESNI) [Bock-2020b], even for innocuous connections.
   The censorship mechanism for China's ESNI censorship differs from how
   China censors SNI-based connections, suggesting that new middleboxes
   were deployed specifically to target ESNI connections.

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4.2.3.3.  Omitted-SNI

   Researchers have observed that some clients omit the SNI extension
   entirely.  This omitted-SNI approach limits the information available
   to a censor.  Like with ESNI, censors can choose to block connections
   that omit the SNI, though this too risks over-blocking.

   Tradeoffs: The approach of censoring all connections that omit the
   SNI field is guaranteed to over-block, though connections that omit
   the SNI field should be relatively rare in the wild.

   Empirical Examples: In the past, researchers have observed censors in
   Russia blocking connections that omit the SNI field [Bock-2020b].

4.2.3.4.  Server Response Certificate

   During the TLS handshake after the TLS Client Hello, the server will
   respond with the TLS certificate.  This certificate also contains the
   domain the client is trying to access, creating another avenue that
   censors can use to perform censorship.  This technique will not work
   in TLS 1.3, as the certificate will be encrypted.

   Tradeoffs: Censoring based on the server certificate requires DPI
   techniques that can be more computationally expensive compared to
   other methods.  Additionally, the certificate is sent later in the
   TLS Handshake compared to the SNI field, forcing the censor to track
   the connection for longer.

   Empirical Examples: Researchers have observed the Reliance Jio ISP in
   India using certificate response fields to censor connections
   [Satija-2021].

4.2.4.  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
   any service that provides utility to users, including everything from
   web sites to storage 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.

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   An increasingly common method of instrumeting content distribution
   consists of hash matching to detect and action images and videos
   known to be restricted either by governments, institutions,
   organizations or the distributor themselves [ekr-2021].

   A different method of instrumenting content distributors consists of
   requiring a distributor to disassociate with some categories of
   users.  See also Section 6.4.

   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 6.2).  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.

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   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
   modification of search engine results in response to either
   copyright, trademark, data protection or defamation concerns
   [EC-2012].

   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 5.3.1.

4.2.5.  DPI Identification

   DPI (deep packet inspection) technically is any kind of packet
   analysis beyond IP address and port number and has become
   computationally feasible as a component of censorship mechanisms 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

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   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
   censorship.

   Tradeoffs: DPI is one of the most expensive identification mechanisms
   and can have a large QoS impact [Porter-2010].  When used as a
   keyword filter for TCP flows, DPI systems can cause also major
   overblocking problems.  Like other techniques, DPI is less useful
   against encrypted data, though DPI can leverage unencrypted elements
   of an encrypted data flow, e.g., the Server Name 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
   identify traffic.  See Section 4.2.3.1 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].

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   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 high-speed packet processing [Hepting-2011].

4.3.  Transport Layer

4.3.1.  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 contain a few invaluable pieces
   of information that must be transparent for traffic to be
   successfully routed: destination and source IP address and port.
   Destination and Source IP are doubly useful, as not only does it
   allow a censor to block undesirable content via IP blocklisting, but
   also allows a censor to identify the IP of the user making the
   request 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.

   Combining IP address, port and protocol information found in the
   transport header, shallow packet inspection can be used by a censor
   to identify specific TCP or UDP endpoints.  UDP endpoint blocking has
   been observed in the context of QUIC blocking [Elmenhorst-2021].

   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 specific route on a router (such as a /32 route for IPv4
   addresses and a /128 route for IPv6 addresses).  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

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   extremely effective because the user needs to proxy their traffic
   through another destination to circumvent this type of
   identification.  In addition, IP blocking is effective against all
   protocols above IP, e.g.  TCP and QUIC.

   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.  HTTPS goes over port 443, with
   similar consequences for the censor except only partial metadata may
   now be available to the censor.  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.  A counter-example is that port 25 (SMTP) has long
   been blocked on residential ISPs' networks to reduce the risk for
   email spam, but in doing so also prohibits residential ISP customers
   from running their own email servers.

4.3.2.  Protocol Identification

   Censors sometimes identify entire protocols to be blocked using a
   variety of traffic characteristics.  For example, Iran impairs the
   performance of HTTPS traffic, a protocol that prevents further
   analysis, to encourage users to switch to HTTP, a protocol that they
   can analyze [Aryan-2012].  A simple protocol identification would be
   to recognize all TCP traffic over port 443 as HTTPS, but more
   sophisticated analysis of the statistical properties of payload data
   and flow behavior, would be more effective, even when port 443 is not
   used [Hjelmvik-2010] [Sandvine-2014].

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

   In active probing, the censor determines whether hosts are running a
   circumvention protocol by trying to initiate communication using the
   circumvention protocol.  If the host and the censor successfully
   negotiate a connection, then the censor conclusively knows that host
   is running a circumvention tool.  China has used active scanning to
   great effect to block Tor [Winter-2012].

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

   Protocol identification is useful for detecting and blocking
   circumvention tools, like Tor, or traffic that is difficult to
   analyze, like VoIP or SSL, because the censor can assume that this
   traffic should be blocked.  However, this can lead to over-blocking
   problems when used with popular protocols.  These methods are
   expensive, both computationally and financially, due to the use of
   statistical analysis, and can be ineffective due to their imprecise
   nature.

   Censors have also used protocol identification in the past in an
   'allowlist' filtering capacity, such as by only allowing specific,
   pre-vetted protocols to be used and blocking any unrecognized
   protocols [Bock-2020].  These protocol filtering approaches can also
   lead to over-blocking if the allowed lists of protocols is too small
   or incomplete, but can be cheap to implement, as many standard
   'allowed' protocols are simple to identify (such as HTTP).

   Empirical Examples: Protocol identification can be easy to detect if
   it is conducted in real time and only a particular protocol is
   blocked, but some types of protocol identification, like active
   scanning, are much more difficult to detect.  Protocol identification
   has been used by Iran to identify and throttle SSH traffic to make it
   unusable [Anonymous-2007] and by China to identify and block Tor
   relays [Winter-2012].  Protocol identification has also been used for
   traffic management, such as the 2007 case where Comcast in the United
   States used RST injection to interrupt BitTorrent Traffic
   [Winter-2012].  In 2020, Iran deployed an allowlist protocol filter,
   which only allowed three protocols to be used (DNS, TLS, and HTTP) on
   specific ports and censored any connection it could not identify
   [Bock-2020].  In 2022, Russia seemed to have used protocol
   identification to block most HTTP/3 connections [Elmenhorst-2022].

4.4.  Residual Censorship

   Another feature of some modern censorship systems is residual
   censorship, a punitive form of censorship whereby after a censor
   disrupts a forbidden connection, the censor continues to target
   subsequent connections, even if they are innocuous [Bock-2021].
   Residual censorship can take many forms and often relies on the
   methods of technical interference described in the next section.

   An important facet of residual censorship is precisely what the
   censor continues to block after censorship is initially triggered.
   There are three common options available to an adversary: 2-tuple

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   (client IP, server IP), 3-tuple (client IP, server IP+port), or
   4-tuple (client IP+port, server IP+port).  Future connections that
   match the tuple of information the censor records will be disrupted
   [Bock-2021].

   Residual censorship can sometimes be difficult to identify and can
   often complicate censorship measurement.

   Trade-offs: The impact of residual censorship is to provide users
   with further discouragement from trying to access forbidden content,
   though it is not clear how successful it is at accomplishing this.

   Empirical Examples: China has used 3-tuple residual censorship in
   conjunction with their HTTP censorship for years and researchers have
   reported seeing similar residual censorship for HTTPS.  China seems
   to use a mix of 3-tuple and 4-tuple residual censorship for their
   censorship of HTTPS with ESNI.  Some censors that perform censorship
   via packet dropping often accidentally implement 4-tuple residual
   censorship, including Iran and Kazakhstan [Bock-2021].

5.  Technical Interference

5.1.  Application Layer

5.1.1.  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
   resolver.

   Responding to a DNS query with an incorrect address can be achieved
   with on-path interception, off-path cache poisoning, and lying by the
   nameserver.

   "DNS mangling" is a network-level technique of on-path interception
   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

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   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 192.0.2.2 for the name "www.uncensored.example" compared
   with "www.censored.example" (censored at the time of writing), we get
   a forged IP address "198.51.100.0" as a response:

   % dig +short +nodnssec @192.0.2.2 A www.uncensored.example
   ;; connection timed out; no servers could be reached

   % dig +short +nodnssec @192.0.2.2 A www.censored.example
   198.51.100.0

   DNS cache poisoning happens off-path and refers to a mechanism where
   a censor interferes with the response sent by an authoritative DNS
   name server to a recursive resolver by responding more quickly than
   the authoritative name server can respond with an alternative IP
   address [Halley-2008].  Cache poisoning occurs after the requested
   site's name servers resolve the request and attempt to forward the
   true IP back to the requesting device; on the return route the
   resolved IP is recursively cached by each DNS server that initially
   forwarded the request.  During this caching process if an undesirable
   keyword is recognized, the resolved IP is "poisoned" and an
   alternative IP (or NXDOMAIN error) is returned more quickly than the
   upstream resolver can respond, causing a forged IP address to be
   cached (and potentially recursively so).  The alternative IPs usually
   direct to a nonsense domain or a warning page.  Alternatively,
   Iranian censorship appears to prevent the communication en-route,
   preventing a response from ever being sent [Aryan-2012].

   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 name server would provide
   [Bortzmeyer-2015].

   Trade-offs: These forms of DNS interference require the censor to
   force a user to traverse a controlled DNS hierarchy (or intervening
   network on which the censor serves as a Active Pervasive Attacker
   [RFC7624] to rewrite DNS responses) for the mechanism to be
   effective.  It can be circumvented by using alternative DNS resolvers
   (such as any of the public DNS resolvers) that may fall outside of
   the jurisdictional control of the censor, or Virtual Private Network
   (VPN) technology.  DNS mangling and cache poisoning also imply
   returning an incorrect IP to those attempting to resolve a domain
   name, but in some cases the destination may be technically
   accessible; over HTTP, for example, the user may have another method
   of obtaining the IP address of the desired site and may be able to

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   access it if the site is configured to be the default server
   listening at this IP address.  Target blocking has also been a
   problem, as occasionally users outside of the censors region will be
   directed through DNS servers or DNS-rewriting network equipment
   controlled by a censor, causing the request to fail.  The ease of
   circumvention paired with the large risk of content blocking and
   target blocking make DNS interference a partial, difficult, and less
   than ideal censorship mechanism.

   Additionally, the above mechanisms rely on DNSSEC not being deployed
   or DNSSEC validation not being active on the client or recursive
   resolver (neither of which are hard to imagine given limited
   deployment of DNSSEC and limited client support for DNSSEC
   validation).  Note that an adversary seeking to merely block
   resolution can serve a DNSSEC record that doesn't validate correctly,
   assuming of course that the client/recursive resolver validates.

   Previously, techniques were used for e.g. censorship that relied on
   DNS requests being passed in cleartext over port 53 [SSAC-109-2020].
   With the deployment of encrypted DNS (e.g., DNS-over-HTTPS [RFC8484])
   these requests are now increasingly passed on port 443 with other
   HTTPS traffic, or in the case of DNS-over-TLS [RFC7858] no longer
   passed in the clear (see also Section 4.3.1).

   Empirical Examples: DNS interference, when properly implemented, is
   easy to identify based on the shortcomings identified above.  Turkey
   relied on DNS interference for its country-wide block of websites
   such Twitter and YouTube for almost week in March of 2014 but the
   ease of circumvention resulted in an increase in the popularity of
   Twitter until Turkish ISPs implementing an IP blocklist to achieve
   the governmental mandate [Zmijewski-2014].  Ultimately, Turkish ISPs
   started hijacking all requests to Google and Level 3's international
   DNS resolvers [Zmijewski-2014].  DNS interference, when incorrectly
   implemented, has resulted in some of the largest "censorship
   disasters".  In January 2014, China started directing all requests
   passing through the Great Fire Wall to a single domain,
   dongtaiwang.com, due to an improperly configured DNS poisoning
   attempt; this incident is thought to be the largest Internet-service
   outage in history [AFP-2014] [Anon-SIGCOMM12].  Countries such as
   China, Iran, Turkey, and the United States have discussed blocking
   entire TLDs as well, but only Iran has acted by blocking all Israeli
   (.il) domains [Albert-2011].  DNS-blocking is commonly deployed in
   European countries to deal with undesirable content, such as child
   abuse content (Norway, United Kingdom, Belgium, Denmark, Finland,
   France, Germany, Ireland, Italy, Malta, the Netherlands, Poland,
   Spain and Sweden [Wright-2013] [Eneman-2010]), online gambling
   (Belgium, Bulgaria, Czech Republic, Cyprus, Denmark, Estonia, France,
   Greece, Hungary, Italy, Latvia, Lithuania, Poland, Portugal, Romania,

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   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]).

5.2.  Transport Layer

5.2.1.  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
   [Aryan-2012].

5.2.2.  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.

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   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.  Notably, packet dropping during the
   handshake or working connection is the only interference technique
   observed for QUIC traffic so far, e.g. in India, Iran, Russia and
   Uganda [Elmenhorst-2021][Elmenhorst-2022].

5.2.3.  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 once the
   connection has been setup.  While QUIC implements a stateless reset
   mechanism, such a reset is only accepted by a peer if the packet ends
   in a previously issued stateless reset token which is hard to guess.
   During the handshake, QUIC only provides effective protection against
   off-path attackers but is vulnerable to injection attacks by
   attackers that have parsed prior packets.  (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 technique employed for censorship.  RST Packet
   Injection is an out-of-band interference mechanism, allowing the

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   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: while the term "blind"
   injection implies the censor doesn't know any sensitive sequencing
   information about the TCP stream they are injecting into, they can
   simply enumerate all ~70000 possible windows; this is particularly
   useful for interrupting encrypted/obfuscated protocols such as SSH or
   Tor [Gilad].  Some censorship evasion systems work by trying to
   confuse the censor into tracking incorrect information, rendering
   their RST Packet Injection useless [Khattak-2013], [Wang-2017],
   [Li-2017], [Bock-2019], [Wang-2020].

   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].

5.3.  Routing Layer

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5.3.1.  Network Disconnection

   While it is perhaps the crudest of all techniques employed for
   censorship, 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 Border 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 by losing the benefits a globally-accessible Internet
   brings.  Network disconnections are also politically expensive -
   citizens used to being able to access Internet platforms and services
   see such disconnections as a loss of civil liberty.  Network
   disconnection is rarely a long-term solution for any 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], and Syria in 2012
   [Thomson-2012].  Russia indicated that it would 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
   [Dada-2017].

5.3.2.  Adversarial Route Announcement

   More fine-grained and potentially wide-spread censorship can be
   achieved with BGP hijacking, which adversarially re-routes BGP IP
   prefixes incorrectly within a region and beyond.  This restricts and
   effectively censors the correctly known location of information that
   flows into or out of a jurisdiction and will similarly prevent people
   from outside your jurisdiction from viewing content generated outside
   your jurisdiction as the adversarial route announcement propagates.
   The first can be achieved by an adversarial BGP announcement of
   incorrect routes that are not intended to leak beyond a jurisdiction,

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   where the latter attacks traffic by deliberately introducing bogus
   BGP announcements that reach the global internet.

   Trade-offs: A global leak of a misrouted website can overwhelm an ISP
   if the website gets a lot of traffic.  It is not a permanent solution
   because incorrect BGP routes that leak globally can be fixed, though
   within a jurisdiction only the ISP/IXP is in a position to correct
   them for local users.

   Empirical examples: In 2008 Pakistan Telecom censored Youtube at the
   request of the Pakistan government by changing its BGP routes for the
   website.  The new routes were announced to the ISP's upstream
   providers and beyond.  The entire Internet began directing Youtube
   routes to Pakistan Telecom and continued doing so for many hours.  In
   2018 nearly all Google services and Google cloud customers like
   Spotify all lost more than one hour of service after it lost control
   of several million of its IP addresses.  Those IP prefixes were being
   misdirected to China Telecom, a Chinese government-owned ISP
   [Google-2018]}, in a manner similar to the BGP hijacking of US
   government and military websites by China Telecom in 2010.  ISPs in
   both Russia (2022) and Myanmar (2021) have tried to hijack the same
   Twitter prefix more than once [MANRS].

5.4.  Multi-layer and Non-layer

5.4.1.  Distributed Denial of Service (DDoS)

   Distributed Denial of Service attacks are a common attack mechanism
   used by "hacktivists" and malicious hackers, but censors have used
   DDoS in the past for a variety of reasons.  There is a huge variety
   of DDoS attacks [Wikip-DoS], but at 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 technique employed for
   censorship.  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.

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

5.4.2.  Censorship in Depth

   Often, censors implement multiple techniques in tandem, creating
   "censorship in depth".  Censorship in depth can take many forms; some
   censors block the same content through multiple techniques (such as
   blocking a domain by DNS, IP blocking, and HTTP simultaneously), some
   deploy parallel systems to improve censorship reliability (such as
   deploying multiple different censorship systems to block the same
   domain), and others can use complimentary systems to limit evasion
   (such as by blocking unwanted protocols entirely, forcing users to
   use other filtered protocols).

   Trade-offs: Censorship in depth can be attractive for censors to
   deploy, as it offers additional guarantees about censorship: even if
   someone evades one type of censorship, they may still be blocked by
   another.  The main drawback to this approach is the cost to initial
   deployment, as it requires the system to deploy multiple censorship
   systems in tandem.

   Empirical Examples: Censorship in depth is present in many large
   censoring nation states today.  Researchers have observed China has
   deployed significant censorship in depth, often censoring the same
   resource across multiple protocols [Chai-2019], [Bock-2020b] or
   deploying additional censorship systems to censor the same content
   and protocol [Bock-2021b].  Iran also has deployed a complimentary
   protocol filter to limit which protocols can be used on certain
   ports, forcing users to rely on protocols their censorship system can
   filter [Bock-2020].

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6.  Non-Technical Interference

6.1.  Manual Filtering

   As the name implies, sometimes manual labor 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
   on its own, or combined with other automated techniques of detection
   that are then followed by an action that would require manual
   confirmation.  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 [BBC-2013b].

6.2.  Self-Censorship

   Self-censorship is difficult to document, as it manifests primarily
   through a lack of undesirable content.  Tools which encourage self-
   censorship are those which may lead a prospective speaker to believe
   that speaking increases the risk of unfavourable outcomes for the
   speaker (technical monitoring, identification requirements, etc.).
   Reporters Without Borders exemplify methods of imposing self-
   censorship in their annual World Press Freedom Index reports
   [RWB2020].

6.3.  Server Takedown

   As mentioned in passing by [Murdoch-2011], 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 -- in cases where a server is virtualized in a cloud
   infrastructure where it may not necessarily have a fixed physical
   location -- the hosting provider can be required to prevent access.

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6.4.  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].

6.5.  Domain-Name Seizures

   Domain names are catalogued in so-called name-servers operated by
   legal entities called registries.  These registries can be made to
   cede control over a domain name to someone other than the entity
   which registered the domain name through a legal procedure grounded
   in either private contracts or public law.  Domain name seizures is
   increasingly used by both public authorities and private entities to
   deal with undesired content dissemination [ICANN2012] [EFF2017].

7.  Future work

   In addition to establishing a thorough resource for describing
   censorship techniques this document implicates critical areas for
   future work.

   Taken as a whole the apparent costs of implementation of censorship
   techniques indicate a need for better classification of censorship
   regimes as they evolve and mature and specifying censorship
   circumvention techniques themselves.  Censors maturity refers to the
   technical maturity required of the censor to perform the specific
   censorship technique.  Future work might classify techniques by
   essentially how hard a censor must work, including what
   infrastructure is required, in order to successfully censor content,
   users or services.

   On circumvention, the increase in protocols leveraging encryption is
   an effective counter-measure against some forms of censorship
   described in this document, but that thorough research on
   circumvention and encryption be left for another document.  Moreover
   the censorship circumvention community has developed an area of
   research on "pluggable transports," which collects, documents and
   makes agile methods for obfuscating the on-path traffic of censorship
   circumvention tools such that it appears indistinguishable from other
   kinds of traffic [Tor-2020].  Those methods would benefit from future
   work in the internet standards community, too.

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   Lastly the empirical examples demonstrate that censorship techniques
   can evolve quickly, and experience shows that this document can only
   be a point-in-time statement.  Future work might extend this document
   with updates and new techniques described using a comparable
   methodology.

8.  Contributors

   This document benefited from discussions with and input from David
   Belson, Stephane Bortzmeyer, Vinicius Fortuna, Gurshabad Grover,
   Andrew McConachie, Martin Nilsson, Michael Richardson, Patrick Vacek
   and Chris Wood.

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   [Grover-2019]
              Grover, G., Singh, K., and E. Hickok, "Reliance Jio is
              using SNI inspection to block websites", 2019,
              <https://cis-india.org/internet-governance/blog/reliance-
              jio-is-using-sni-inspection-to-block-websites>.

   [Guardian-2014]
              The Gaurdian, "Chinese blogger jailed under crackdown on
              'internet rumours'", 2014,
              <http://www.theguardian.com/world/2014/apr/17/chinese-
              blogger-jailed-crackdown-internet-rumours-qin-zhihui>.

   [HADOPI-2020]
              Haute Autorité pour la Diffusion des oeuvres et la
              Protection des Droits sur Internet, "Présentation", 2020,
              <https://www.hadopi.fr/en/node/3668>.

Hall, et al.              Expires 14 July 2023                 [Page 35]
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   [Halley-2008]
              Halley, B., "How DNS cache poisoning works", 2014,
              <https://www.networkworld.com/article/2277316/tech-
              primers/tech-primers-how-dns-cache-poisoning-works.html>.

   [Heacock-2009]
              Heacock, R., "China Shuts Down Internet in Xinjiang Region
              After Riots", 2009, <https://opennet.net/blog/2009/07/
              china-shuts-down-internet-xinjiang-region-after-riots>.

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              Wikipedia, "Hepting vs. AT&T", 2011,
              <https://en.wikipedia.org/wiki/Hepting_v._AT%26T>.

   [Hertel-2015]
              Hertel, O., "Comment les autorités peuvent bloquer un site
              Internet", 2015, <https://www.sciencesetavenir.fr/high-
              tech/comment-les-autorites-peuvent-bloquer-un-site-
              internet_35828>.

   [Hjelmvik-2010]
              Hjelmvik, E., "Breaking and Improving Protocol
              Obfuscation", 2010,
              <https://www.iis.se/docs/hjelmvik_breaking.pdf>.

   [Hopkins-2011]
              Hopkins, C., "Communications Blocked in Libya, Qatari
              Blogger Arrested: This Week in Online Tyranny", 2011,
              <http://readwrite.com/2011/03/03/
              communications_blocked_in_libya_this_week_in_onlin>.

   [Husak-2016]
              Husak, M., Cermak, M., Jirsik, T., and P. Celeda, "HTTPS
              traffic analysis and client identification using passive
              SSL/TLS fingerprinting", 2016,
              <https://link.springer.com/article/10.1186/
              s13635-016-0030-7>.

   [I-D.ietf-quic-transport]
              Iyengar, J. and M. Thomson, "QUIC: A UDP-Based Multiplexed
              and Secure Transport", Work in Progress, Internet-Draft,
              draft-ietf-quic-transport-34, 14 January 2021,
              <https://www.ietf.org/archive/id/draft-ietf-quic-
              transport-34.txt>.

   [I-D.ietf-tls-esni]
              Rescorla, E., Oku, K., Sullivan, N., and C. A. Wood, "TLS
              Encrypted Client Hello", Work in Progress, Internet-Draft,

Hall, et al.              Expires 14 July 2023                 [Page 36]
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              draft-ietf-tls-esni-15, 3 October 2022,
              <https://www.ietf.org/archive/id/draft-ietf-tls-esni-
              15.txt>.

   [I-D.ietf-tls-sni-encryption]
              Huitema, C. and E. Rescorla, "Issues and Requirements for
              Server Name Identification (SNI) Encryption in TLS", Work
              in Progress, Internet-Draft, draft-ietf-tls-sni-
              encryption-09, 28 October 2019,
              <https://www.ietf.org/archive/id/draft-ietf-tls-sni-
              encryption-09.txt>.

   [ICANN-SSAC-2012]
              ICANN Security and Stability Advisory Committee (SSAC),
              "SAC 056: SSAC Advisory on Impacts of Content Blocking via
              the Domain Name System", 2012,
              <https://www.icann.org/en/system/files/files/sac-
              056-en.pdf>.

   [ICANN2012]
              ICANN Security and Stability Advisory Committee, "Guidance
              for Preparing Domain Name Orders, Seizures & Takedowns",
              2012, <https://www.icann.org/en/system/files/files/
              guidance-domain-seizures-07mar12-en.pdf>.

   [Jones-2014]
              Jones, B., "Automated Detection and Fingerprinting of
              Censorship Block Pages", 2014,
              <http://conferences2.sigcomm.org/imc/2014/papers/
              p299.pdf>.

   [Khattak-2013]
              Khattak, S., "Towards Illuminating a Censorship Monitor's
              Model to Facilitate Evasion", 2013, <http://0b4af6cdc2f0c5
              998459-c0245c5c937c5dedcca3f1764ecc9b2f.r43.cf2.rackcdn.co
              m/12389-foci13-khattak.pdf>.

   [Knight-2005]
              Knight, W., "Iranian net censorship powered by US
              technology", 2005, <https://www.newscientist.com/article/
              dn7589-iranian-net-censorship-powered-by-us-technology/>.

   [Knockel-2021]
              Knockel, J. and L. Ruan, "Measuring QQMail's automated
              email censorship in China", 2021,
              <https://dl.acm.org/doi/10.1145/3473604.3474560>.

Hall, et al.              Expires 14 July 2023                 [Page 37]
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   [Kopel-2013]
              Kopel, K., "Operation Seizing Our Sites: How the Federal
              Government is Taking Domain Names Without Prior Notice",
              2013, <http://dx.doi.org/doi:10.15779/Z384Q3M>.

   [Kravtsova-2012]
              Kravtsova, Y., "Cyberattacks Disrupt Opposition's
              Election", 2012,
              <http://www.themoscowtimes.com/news/article/cyberattacks-
              disrupt-oppositions-election/470119.html>.

   [Leyba-2019]
              Leyba, K., Edwards, B., Freeman, C., Crandall, J., and S.
              Forrest, "Borders and Gateways: Measuring and Analyzing
              National AS Chokepoints", 2019,
              <https://forrest.biodesign.asu.edu/data/publications/2019-
              compass-chokepoints.pdf>.

   [Li-2017]  Li, F., Razaghpanah, A., Kakhki, A., Niaki, A., Choffnes,
              D., Gill, P., and A. Mislove, "lib•erate, (n) : A library
              for exposing (traffic-classification) rules and avoiding
              them efficiently", 2017,
              <https://david.choffnes.com/pubs/liberate-imc17.pdf>.

   [Lomas-2019]
              Lomas, N., "Github removes Tsunami Democràtic’s APK after
              a takedown order from Spain", 2019,
              <https://techcrunch.com/2019/10/30/github-removes-tsunami-
              democratics-apk-after-a-takedown-order-from-spain/>.

   [MANRS]    Siddiqui, A., "Lesson Learned: Twitter Shored Up Its
              Routing Security", 2022, <https://www.manrs.org/2022/03/
              lesson-learned-twitter-shored-up-its-routing-security/>.

   [Marczak-2015]
              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”",
              2015,
              <https://www.usenix.org/system/files/conference/foci15/
              foci15-paper-marczak.pdf>.

   [Muncaster-2013]
              Muncaster, P., "Malaysian election sparks web blocking/
              DDoS claims", 2013,
              <http://www.theregister.co.uk/2013/05/09/
              malaysia_fraud_elections_ddos_web_blocking/>.

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   [Murdoch-2011]
              Murdoch, S. J. and R. Anderson, "Access Denied: Tools and
              Technology of Internet Filtering", 2011,
              <http://access.opennet.net/wp-content/uploads/2011/12/
              accessdenied-chapter-3.pdf>.

   [NA-SK-2019]
              Morgus, R., Sherman, J., and S. Nam, "Analysis: South
              Korea's New Tool for Filtering Illegal Internet Content",
              2019, <https://www.newamerica.org/cybersecurity-
              initiative/c2b/c2b-log/analysis-south-koreas-sni-
              monitoring/>.

   [Nabi-2013]
              Nabi, Z., "The Anatomy of Web Censorship in Pakistan",
              2013, <http://0b4af6cdc2f0c5998459-c0245c5c937c5dedcca3f17
              64ecc9b2f.r43.cf2.rackcdn.com/12387-foci13-nabi.pdf>.

   [Netsec-2011]
              n3t2.3c, "TCP-RST Injection", 2011,
              <https://nets.ec/TCP-RST_Injection>.

   [OONI-2018]
              Evdokimov, L., "Iran Protests: DPI blocking of Instagram
              (Part 2)", 2018,
              <https://ooni.org/post/2018-iran-protests-pt2/>.

   [OONI-2019]
              Singh, S., Filastò, A., and M. Xynou, "China is now
              blocking all language editions of Wikipedia", 2019,
              <https://ooni.org/post/2019-china-wikipedia-blocking/>.

   [Orion-2013]
              Orion, E., "Zimbabwe election hit by hacking and DDoS
              attacks", 2013,
              <http://www.theinquirer.net/inquirer/news/2287433/
              zimbabwe-election-hit-by-hacking-and-ddos-attacks>.

   [Patil-2019]
              Patil, S. and N. Borisov, "What Can You Learn from an
              IP?", 2019, <https://irtf.org/anrw/2019/
              anrw2019-final44-acmpaginated.pdf>.

   [Porter-2010]
              Porter, T., "The Perils of Deep Packet Inspection", 2010,
              <http://www.symantec.com/connect/articles/perils-deep-
              packet-inspection>.

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   [Rambert-2021]
              Rampert, R., Weinberg, Z., Barradas, D., and N. Christin,
              "Chinese Wall or Swiss Cheese? Keyword filtering in the
              Great Firewall of China", 2021,
              <https://www.andrew.cmu.edu/user/nicolasc/publications/
              Rambert-WWW21.pdf>.

   [Reda-2017]
              Reda, J., "New EU law prescribes website blocking in the
              name of 'consumer protection'", 2017,
              <https://juliareda.eu/2017/11/eu-website-blocking/>.

   [RFC0793]  Postel, J., "Transmission Control Protocol", RFC 793,
              DOI 10.17487/RFC0793, September 1981,
              <https://www.rfc-editor.org/info/rfc793>.

   [RFC6066]  Eastlake 3rd, D., "Transport Layer Security (TLS)
              Extensions: Extension Definitions", RFC 6066,
              DOI 10.17487/RFC6066, January 2011,
              <https://www.rfc-editor.org/info/rfc6066>.

   [RFC7624]  Barnes, R., Schneier, B., Jennings, C., Hardie, T.,
              Trammell, B., Huitema, C., and D. Borkmann,
              "Confidentiality in the Face of Pervasive Surveillance: A
              Threat Model and Problem Statement", RFC 7624,
              DOI 10.17487/RFC7624, August 2015,
              <https://www.rfc-editor.org/info/rfc7624>.

   [RFC7754]  Barnes, R., Cooper, A., Kolkman, O., Thaler, D., and E.
              Nordmark, "Technical Considerations for Internet Service
              Blocking and Filtering", RFC 7754, DOI 10.17487/RFC7754,
              March 2016, <https://www.rfc-editor.org/info/rfc7754>.

   [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>.

   [RFC8484]  Hoffman, P. and P. McManus, "DNS Queries over HTTPS
              (DoH)", RFC 8484, DOI 10.17487/RFC8484, October 2018,
              <https://www.rfc-editor.org/info/rfc8484>.

   [RSF-2005] Reporters Sans Frontieres, "Technical ways to get around
              censorship", 2005, <http://archives.rsf.org/print-
              blogs.php3?id_article=15013>.

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   [Rushe-2015]
              Rushe, D., "Bing censoring Chinese language search results
              for users in the US", 2013,
              <http://www.theguardian.com/technology/2014/feb/11/bing-
              censors-chinese-language-search-results>.

   [RWB2020]  Reporters Without Borders, "2020 World Press Freedom
              Index: Entering a decisive decade for journalism,
              exacerbated by coronavirus", 2020, <https://rsf.org/
              en/2020-world-press-freedom-index-entering-decisive-
              decade-journalism-exacerbated-coronavirus>.

   [Sandvine-2014]
              Sandvine, "Technology Showcase on Traffic Classification:
              Why Measurements and Freeform Policy Matter", 2014,
              <https://www.sandvine.com/downloads/general/technology/
              sandvine-technology-showcases/sandvine-technology-
              showcase-traffic-classification.pdf>.

   [Satija-2021]
              Satija, S. and R. Chatterjee, "BlindTLS: Circumventing
              TLS-based HTTPS censorship", 2021,
              <https://sambhav.info/files/blindtls-foci21.pdf>.

   [Schoen-2007]
              Schoen, S., "EFF tests agree with AP: Comcast is forging
              packets to interfere with user traffic", 2007,
              <https://www.eff.org/deeplinks/2007/10/eff-tests-agree-ap-
              comcast-forging-packets-to-interfere>.

   [Schone-2014]
              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-
              interview/exclusive-snowden-docs-show-uk-spies-attacked-
              anonymous-hackers-n21361>.

   [Senft-2013]
              Senft, A., "Asia Chats: Analyzing Information Controls and
              Privacy in Asian Messaging Applications", 2013,
              <https://citizenlab.org/2013/11/asia-chats-analyzing-
              information-controls-privacy-asian-messaging-
              applications/>.

   [Shbair-2015]
              Shbair, W. M., Cholez, T., Goichot, A., and I. Chrisment,
              "Efficiently Bypassing SNI-based HTTPS Filtering", 2015,
              <https://hal.inria.fr/hal-01202712/document>.

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   [SIDN2020] Moura, G., "Detecting and Taking Down Fraudulent Webshops
              at the .nl ccTLD", 2020,
              <https://labs.ripe.net/Members/giovane_moura/detecting-
              and-taking-down-fraudulent-webshops-at-a-cctld>.

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

   [Sophos-2015]
              Sophos, "Understanding Sophos Web Filtering", 2015,
              <https://www.sophos.com/en-us/support/
              knowledgebase/115865.aspx>.

   [SSAC-109-2020]
              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-
              109-en.pdf>.

   [Tang-2016]
              Tang, C., "In-depth analysis of the Great Firewall of
              China", 2016,
              <https://www.cs.tufts.edu/comp/116/archive/fall2016/
              ctang.pdf>.

   [Thomson-2012]
              Thomson, I., "Syria Cuts off Internet and Mobile
              Communication", 2012,
              <http://www.theregister.co.uk/2012/11/29/
              syria_internet_blackout/>.

   [Tor-2020] The Tor Project, "Tor: Pluggable Transports", 2020,
              <https://2019.www.torproject.org/docs/pluggable-
              transports.html.en>.

   [Trustwave-2015]
              Trustwave, "Filter: SNI extension feature and HTTPS
              blocking", 2015,
              <https://www3.trustwave.com/software/8e6/hlp/r3000/
              files/1system_filter.html>.

   [Tschantz-2016]
              Tschantz, M., Afroz, S., Anonymous, A., and V. Paxson,
              "SoK: Towards Grounding Censorship Circumvention in
              Empiricism", 2016,
              <https://oaklandsok.github.io/papers/tschantz2016.pdf>.

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   [Verkamp-2012]
              Verkamp, J. P. and M. Gupta, "Inferring Mechanics of Web
              Censorship Around the World", 2012,
              <https://www.usenix.org/system/files/conference/foci12/
              foci12-final1.pdf>.

   [Victor-2019]
              Victor, D., "Blizzard Sets Off Backlash for Penalizing
              Hearthstone Gamer in Hong Kong", 2019,
              <https://www.nytimes.com/2019/10/09/world/asia/blizzard-
              hearthstone-hong-kong.html>.

   [Villeneuve-2011]
              Villeneuve, N., "Open Access: Chapter 8, Control and
              Resistance, Attacks on Burmese Opposition Media", 2011,
              <http://access.opennet.net/wp-content/uploads/2011/12/
              accesscontested-chapter-08.pdf>.

   [VonLohmann-2008]
              VonLohmann, F., "FCC Rules Against Comcast for BitTorrent
              Blocking", 2008, <https://www.eff.org/deeplinks/2008/08/
              fcc-rules-against-comcast-bit-torrent-blocking>.

   [Wagner-2009]
              Wagner, B., "Deep Packet Inspection and Internet
              Censorship: International Convergence on an ‘Integrated
              Technology of Control'", 2009,
              <http://advocacy.globalvoicesonline.org/wp-
              content/uploads/2009/06/deeppacketinspectionandinternet-
              censorship2.pdf>.

   [Wagstaff-2013]
              Wagstaff, J., "In Malaysia, online election battles take a
              nasty turn", 2013,
              <http://www.reuters.com/article/2013/05/04/uk-malaysia-
              election-online-idUKBRE94309G20130504>.

   [Wang-2017]
              Wang, Z., Cao, Y., Qian, Z., Song, C., and S.
              Krishnamurthy, "Your State is Not Mine: A Closer Look at
              Evading Stateful Internet Censorship", 2017,
              <https://www.cs.ucr.edu/~zhiyunq/pub/
              imc17_censorship_tcp.pdf>.

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   [Wang-2020]
              Wang, Z., Zhu, S., Cao, Y., Qian, Z., Song, C.,
              Krishnamurthy, S., Chan, K., and T. Braun, "SYMTCP:
              Eluding Stateful Deep Packet Inspection with Automated
              Discrepancy Discovery", 2020,
              <https://www.cs.ucr.edu/~zhiyunq/pub/ndss20_symtcp.pdf>.

   [Weaver-2009]
              Weaver, N., Sommer, R., and V. Paxson, "Detecting Forged
              TCP Packets", 2009, <http://www.icir.org/vern/papers/
              reset-injection.ndss09.pdf>.

   [Whittaker-2013]
              Whittaker, Z., "1,168 keywords Skype uses to censor,
              monitor its Chinese users", 2013,
              <http://www.zdnet.com/1168-keywords-skype-uses-to-censor-
              monitor-its-chinese-users-7000012328/>.

   [Wikip-DoS]
              Wikipedia, "Denial of Service Attacks", 2016,
              <https://en.wikipedia.org/w/index.php?title=Denial-of-
              service_attack&oldid=710558258>.

   [Wilde-2012]
              Wilde, T., "Knock Knock Knockin' on Bridges Doors", 2012,
              <https://blog.torproject.org/blog/knock-knock-knockin-
              bridges-doors>.

   [Winter-2012]
              Winter, P., "How China is Blocking Tor", 2012,
              <http://arxiv.org/pdf/1204.0447v1.pdf>.

   [WP-Def-2020]
              Wikipedia contributors, "Censorship", 2020,
              <https://en.wikipedia.org/w/
              index.php?title=Censorship&oldid=943938595>.

   [Wright-2013]
              Wright, J. and Y. Breindl, "Internet filtering trends in
              liberal democracies: French and German regulatory
              debates", 2013,
              <https://policyreview.info/articles/analysis/internet-
              filtering-trends-liberal-democracies-french-and-german-
              regulatory-debates>.

   [Zhu-2011] Zhu, T., "An Analysis of Chinese Search Engine Filtering",
              2011,
              <http://arxiv.org/ftp/arxiv/papers/1107/1107.3794.pdf>.

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   [Zmijewski-2014]
              Zmijewski, E., "Turkish Internet Censorship Takes a New
              Turn", 2014,
              <https://blogs.oracle.com/internetintelligence/turkish-
              internet-censorship-takes-a-new-turn>.

Authors' Addresses

   Joseph Lorenzo Hall
   Internet Society
   Email: hall@isoc.org

   Michael D. Aaron
   CU Boulder
   Email: michael.drew.aaron@gmail.com

   Amelia Andersdotter
   Email: amelia.ietf@andersdotter.cc

   Ben Jones
   Email: ben.jones.irtf@gmail.com

   Nick Feamster
   U Chicago
   Email: feamster@uchicago.edu

   Mallory Knodel
   Center for Democracy & Technology
   Email: mknodel@cdt.org

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