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Internet Research Task Force (IRTF) J. L. Hall
Request for Comments: 9505 Internet Society
Category: Informational M. D. Aaron
ISSN: 2070-1721 CU Boulder
A. Andersdotter
B. Jones
N. Feamster
U Chicago
M. Knodel
Center for Democracy & Technology
November 2023
A Survey of Worldwide Censorship Techniques
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 document is not an Internet Standards Track specification; it is
published for informational purposes.
This document is a product of the Internet Research Task Force
(IRTF). The IRTF publishes the results of Internet-related research
and development activities. These results might not be suitable for
deployment. This RFC represents the consensus of the Privacy
Enhancements and Assessments Research Group of the Internet Research
Task Force (IRTF). Documents approved for publication by the IRSG
are not candidates for any level of Internet Standard; see Section 2
of RFC 7841.
Information about the current status of this document, any errata,
and how to provide feedback on it may be obtained at
https://www.rfc-editor.org/info/rfc9505.
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.
Table of Contents
1. Introduction
2. Terminology
3. Technical Prescription
4. Technical Identification
4.1. Points of Control
4.2. Application Layer
4.2.1. HTTP Request Header Identification
4.2.2. HTTP Response Header Identification
4.2.3. Transport Layer Security (TLS)
4.2.4. Instrumenting Content Distributors
4.2.5. DPI Identification
4.3. Transport Layer
4.3.1. Shallow Packet Inspection and Transport Header
Identification
4.3.2. Protocol Identification
4.4. Residual Censorship
5. Technical Interference
5.1. Application Layer
5.1.1. DNS Interference
5.2. Transport Layer
5.2.1. Performance Degradation
5.2.2. Packet Dropping
5.2.3. RST Packet Injection
5.3. Routing Layer
5.3.1. Network Disconnection
5.3.2. Adversarial Route Announcement
5.4. Multi-layer and Non-layer
5.4.1. Distributed Denial of Service (DDoS)
5.4.2. Censorship in Depth
6. Non-technical Interference
6.1. Manual Filtering
6.2. Self-Censorship
6.3. Server Takedown
6.4. Notice and Takedown
6.5. Domain Name Seizures
7. Future Work
8. IANA Considerations
9. Security Considerations
10. Informative References
Acknowledgments
Authors' Addresses
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, or inconvenient
[WP-Def-2020]. Although censors that engage in censorship must do so
through legal, martial, 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 trade-offs 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. This 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 undesirable. Interference is the process by which censors
intercede in communication and prevent 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
area in the effort to identify content deemed as morally or
commercially harmful to companies or consumers in some jurisdictions
[SIDN-2020].
There are typically a few types of blocklist elements: keyword,
domain name, protocol, or IP address. Keyword and domain name
blocking take place at the application level, e.g., HTTP; protocol
blocking often occurs using deep packet inspection (DPI) 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 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, the Ministry of Culture and Islamic
Guidance in Iran, and the organizations specific to copyright law in
France [HADOPI] and consumer protection law across the EU
[Reda-2017].
Content-layer filtering of images and video requires 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 ecosystem (e.g., domain name system (DNS) or certificate
authorities (CAs)), 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 that censors may
use for interception mechanisms, including, though not limited to,
the following:
Internet Backbone:
If a censor controls elements of Internet network infrastructure,
such as the international gateways into a region or Internet
Exchange Points (IXPs), those choke points can be used to filter
undesirable traffic that is traveling into and out of the region
by packet sniffing and port mirroring. Censorship at gateways 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,
which would have to be accomplished at exchange points or other
network aggregation points. Some national network designs
naturally serve as more effective choke points and points of
control [Leyba-2019].
Internet Service Providers (ISPs):
ISPs 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.
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 schoolchildren, 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 QoS. 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 allows for easier interference.
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 or Local
Internet Registries (RIRs or LIRs) that issue Route Origin
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 it may not have been possible before. CAs may also be
forced to revoke certificates. This may lead to adversarial
traffic routing, 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 discussions of moral imperatives
to use censorship tools.
Content Sites:
On the service side of communications lie many platforms that
publish user-generated content and 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.
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 has exacerbated 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 Sections 4.2.1
and 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 trade-offs 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 (for example, GET /page) as well. This
identification technique is usually paired with transport header
identification (see Section 4.3.1) for a more robust method.
Trade-offs: HTTP request header identification is a technically
straightforward identification method that can be easily implemented
at the backbone or ISP level. The hardware needed for this sort of
identification is cheap and easy to acquire, making it desirable when
budget and scope are a concern. HTTPS (Hypertext Transport Protocol
Secure) 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 and/or 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-2013]. Commercial technologies are
often purchased by censors [Dalek-2013]. These commercial
technologies use a combination of HTTP request header 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, HTTP response
header identification uses information sent in response by the server
to client to identify undesirable content.
Trade-offs: 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.
4.2.3. Transport Layer Security (TLS)
Similar to HTTP, censors have deployed a variety of techniques
towards censoring TLS (and by extension HTTPS). Most of these
techniques relate to the Server Name Indication (SNI) field,
including censoring SNI, Encrypted SNI (ESNI), 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 ClientHello message which domain name it
seeks to connect to (so that the server can respond with the
appropriate TLS certificate) using, the SNI TLS extension [RFC6066].
The ClientHello message is unencrypted for TCP-based TLS. When using
QUIC, the ClientHello 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 ongoing standardization efforts in the TLS
Working Group to encrypt SNI [RFC8744] [TLS-ESNI], and recent
research shows promising results in the use of ESNI 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.
Trade-offs: 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
expensive in terms of computational complexity and infrastructure,
especially when applied to QUIC where DPI requires key extraction and
decryption of the ClientHello in order to read the SNI. Improper
configuration of an SNI-based block can result in significant over-
blocking, e.g., when a second-level domain like
"populardomain.example" is inadvertently blocked. In the case of
ESNI, 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-2023]
[Shbair-2015]. The governments of China, Egypt, Iran, Qatar, South
Korea, Turkey, Turkmenistan, and the United Arab Emirates 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 was
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 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 over-
blocking for the censor but can be worth the cost if ESNI is not yet
widely deployed within the country. ECH is the emerging standard for
protecting the entire TLS ClientHello, but it is not yet widely
deployed.
Trade-offs: The cost to censoring 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 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.
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.
Trade-offs: 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 ClientHello, 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.
Trade-offs: 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 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 websites to storage to locally installed programs.
A commonly used method of instrumenting content distributors consists
of keyword identification to detect restricted terms on their
platforms. Governments may provide the terms on such keyword lists.
Alternatively, the content provider may be expected to come up with
their own list.
An increasingly common method of instrumenting content distribution
consists of hash matching to detect and take action against 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.
Trade-offs: 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 websites 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 trade-offs 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 page 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-2014] [Cheng-2010]
[Whittaker-2013] [BBC-2013] [Condliffe-2013]. To demonstrate the
prevalence of this type of keyword identification, we look to search
engine censorship.
Search engine censorship demonstrates keyword identification by
content providers and can be regional or worldwide. Implementation
is occasionally voluntary, but normally it is based on laws and
regulations of the country a search engine is operating in. The
keyword blocklists are most likely maintained by the search engine
provider. China is known to require search engine providers to
"voluntarily" maintain search term blocklists to acquire and keep an
Internet Content Provider (ICP) license [Cheng-2010]. It is clear
these blocklists are maintained by each search engine provider based
on the slight variations in the intercepted searches [Zhu-2011]
[Whittaker-2013]. The United Kingdom has been pushing search engines
to self-censor with the threat of litigation if they do not do it
themselves: Google and Microsoft have agreed to block more than
100,000 queries in the U.K. to help combat abuse [BBC-2013]
[Condliffe-2013]. European Union law, as well as United States 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-2014] 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 Catalan 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 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 technologies because it can leverage additional packet
and flow characteristics, e.g., packet sizes and timings, when
identifying content. To prevent substantial 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 (IDSs) configured for censorship.
Trade-offs: DPI is one of the most expensive identification
mechanisms and can have a large QoS impact [Porter-2005]. When used
as a keyword filter for TCP flows, DPI systems can cause also major
over-blocking 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 to inject TCP RSTs
and bad DNS responses, respectively, into connections [Crandall-2010]
[Clayton-2006] [Anonymous-2014].
Empirical Examples: Several studies have found evidence of censors
using DPI for censoring content and tools. Clayton et al., Crandal
et al., Anonymous, and Khattak et al., all explored the GFW
[Crandall-2010] [Clayton-2006] [Anonymous-2014]. Khattak et al. even
probed the firewall to discover implementation details like how much
state it stores [Khattak-2013]. The Tor project claims that China,
Iran, Ethiopia, and others must have used DPI to block the obfs2
protocol [Wilde-2012]. Malaysia has been accused of using targeted
DPI, paired with DDoS, to identify and subsequently attack pro-
opposition material [Wagstaff-2013]. It also seems likely that
organizations that are 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 do they
allow a censor to block undesirable content via IP blocklisting but
also allow 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.
By 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 in some routers, 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 over-blocking and cannot deal with some services like
Content Distribution Networks (CDNs) that host content at hundreds or
thousands of IP addresses. Despite these limitations, IP blocking is
extremely effective because the user needs to proxy their traffic
through another destination to circumvent this type of
identification. 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 counterexample is that port 25 (SMTP) has
long been blocked on residential ISP networks to reduce the risk of
email spam, but doing this 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-2013]. A simple protocol identification would be
to recognize all TCP traffic over port 443 as HTTPS, but a 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-2015].
If censors can detect circumvention tools, they can block them.
Therefore, censors like China are extremely interested in identifying
the protocols for censorship circumvention tools. In recent years,
this has devolved into a competition between censors and
circumvention tool developers. As part of this competition, 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 the
host is running a circumvention tool. China has used active scanning
to great effect to block Tor [Winter-2012].
Trade-offs: Protocol identification 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 Voice over IP (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 are 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. However, 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 Secure Shell (SSH)
protocol traffic to make it unusable [Van-der-Sar-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
(injection of a TCP RST packet into the stream) 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
(client IP, server IP), 3-tuple (client IP, server IP, server port),
or 4-tuple (client IP, client port, server IP, server 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, or lying by the
name server.
"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. Some Chinese networks, for example, do
this. (We are not aware of any other wide-scale uses of mangling.)
On those Chinese networks, each DNS request in transit is examined
(presumably by network inspection technologies such as DPI), and if
it matches a censored domain, a false response is injected. End
users can see this technique in action by simply sending DNS requests
to any unused IP address in China (see example below). If it is not
a censored name, there will be no response. If it is censored, a
forged response will be returned. For example, using the command-
line dig utility to query an unused IP address in China of 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-2013].
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 an 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 an active pervasive attacker
[RFC7624] to rewrite DNS responses) for the mechanism to be
effective. DNS interference 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. For example, over HTTP, the user may have another method
of obtaining the IP address of the desired site and may be able to
access it if the site is configured to be the default server
listening at this IP address. Target blocking has also been a
problem, as occasionally users outside of the censor's 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 is 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 or recursive resolver validates.
Previously, techniques were used for 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,
including Twitter and YouTube, for almost a week in March of 2014.
The ease of circumvention resulted in an increase in the popularity
of Twitter until Turkish ISPs implemented 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, Turkey, and the United States have discussed blocking entire
Top-Level Domains (TLDs) as well [Albert-2011]. DNS blocking is
commonly deployed in European countries to deal with undesirable
content, such as
* child abuse content (Norway, United Kingdom, Belgium, Denmark,
Finland, France, Germany, Ireland, Italy, Malta, the Netherlands,
Poland, Spain, and Sweden [Wright-2013] [Eneman-2010]),
* online gambling (Belgium, Bulgaria, Czech Republic, Cyprus,
Denmark, Estonia, France, Greece, Hungary, Italy, Latvia,
Lithuania, Poland, Portugal, Romania, Slovakia, Slovenia, and
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 to 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-2013].
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.
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 subdomain; 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 almost 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 timeout requests it leaves in its wake. The
Great Firewall of China has been observed using packet dropping as
one of its primary technical censorship mechanisms [Ensafi-2013].
Iran has also used packet dropping as the mechanism for throttling
SSH [Aryan-2013]. 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 to date (e.g., in India, Iran, Russia, and Uganda
[Elmenhorst-2021] [Elmenhorst-2022]).
5.2.3. RST Packet Injection
Packet injection, generally, refers to a machine-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 a
TCP connection know the other side has stopped sending information
and that 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 set up. 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 difficult 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 [RFC9000] 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
avoidance of the QoS bottleneck that 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 machine-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 endpoint accepts a RST packet as
legitimate; this generally implies a correct IP, port, and TCP
sequence number. The sequence number is the hardest to get correct,
as [RFC9293] specifies that a RST packet should be in sequence to be
accepted, although that RFC also recommends allowing in-window
packets. This in-window recommendation is important; 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], subsequently leading 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
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 entity withdraws all of the Border Gateway Protocol
(BGP) prefixes routing through the censor's country.
Trade-offs: The impact of 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 as
citizens accustomed to accessing 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 civil
unrest in a country.
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 when the junta in Myanmar employed
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
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 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
that 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,
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, but
leaks within a jurisdiction can only be corrected by an ISP/IXP 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 Google 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 [Siddiqui-2022].
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. Censors have also used
DDoS in the past for a variety of reasons. There is a wide variety
of DDoS attacks [Wikip-DoS]. However, at a high level, two possible
impacts from the attack tend to occur: a flood attack results in the
service being unusable while resources are being spent to flood the
service, and 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 (not just regional access) to undesirable
content for a limited period of time. Temporal impermanence is
really the only uniquely beneficial feature of DDoS as a technique
employed for censorship. The resources required to carry out a
successful DDoS against major targets are computationally expensive,
usually requiring rental or ownership of a malicious distributed
platform such as a botnet, and they are imprecise. DDoS is an
incredibly crude censorship technique and appears to largely be used
as a timely, easy-to-access mechanism for blocking undesirable
content for a limited period of time.
Empirical Examples: In 2012, the U.K.'s signals intelligence
organization, the Government Communications Headquarters (GCHQ), used
DDoS to temporarily shutdown Internet Relay Chat (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 [NBC-2014] [CERT-2000]. Dissenting opinion websites are
frequently victims of DDoS around politically sensitive events like
the DDoS 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 (dubbed "Great
Cannon"), collocated with the Great Firewall, 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 that 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].
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 or
ISP level. China's army of monitors is a good example [BBC-2013b],
but more commonly, manual filtering occurs on an institutional level.
ICPs, 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 that encourage self-
censorship may lead a prospective speaker to believe that speaking
increases the risk of unfavorable 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 [RWB-2020].
6.3. Server Takedown
As mentioned in passing by [Murdoch-2008], 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.
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 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 that
registered the domain name through a legal procedure grounded in
either private contracts or public law. Domain name seizure is
increasingly used by both public authorities and private entities to
deal with undesired content dissemination [ICANN-2012] [EFF-2017].
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 better specification of
censorship circumvention techniques themselves. Censor 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 countermeasure against some forms of censorship
described in this document, but that thorough research on
circumvention and encryption is left for another document. Moreover,
the censorship circumvention community has developed an area of
research on "pluggable transports," which collect, document, and make
agile methods for obfuscating the on-path traffic of censorship
circumvention tools such that it appears indistinguishable from other
kinds of traffic [Tor-2019]. Those methods would benefit from future
work in the Internet standards community, too.
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. IANA Considerations
This document has no IANA actions.
9. Security Considerations
This document is a survey of existing literature on network
censorship techniques. As such, it does not introduce any new
security considerations to be taken into account beyond what is
already discussed in each paper surveyed.
10. Informative References
[AFNIC-2013]
AFNIC, "Report of the AFNIC Scientific Council:
Consequences of DNS-based Internet filtering", January
2013,
<http://www.afnic.fr/medias/documents/conseilscientifique/
SC-consequences-of-DNS-based-Internet-filtering.pdf>.
[AFP-2014] AFP, "China Has Massive Internet Breakdown Reportedly
Caused By Their Own Censoring Tools", January 2014,
<http://www.businessinsider.com/chinas-internet-breakdown-
reportedly-caused-by-censoring-tools-2014-1>.
[Albert-2011]
Albert, K., "DNS Tampering and the new ICANN gTLD Rules",
June 2011, <https://opennet.net/blog/2011/06/dns-
tampering-and-new-icann-gtld-rules>.
[Anon-SIGCOMM12]
Anonymous, "The Collateral Damage of Internet Censorship
by DNS Injection", July 2012,
<http://www.sigcomm.org/sites/default/files/ccr/
papers/2012/July/2317307-2317311.pdf>.
[Anonymous-2013]
Anonymous, "GitHub blocked in China - how it happened, how
to get around it, and where it will take us", January
2013, <https://en.greatfire.org/blog/2013/jan/github-
blocked-china-how-it-happened-how-get-around-it-and-where-
it-will-take-us>.
[Anonymous-2014]
Anonymous, "Towards a Comprehensive Picture of the Great
Firewall's DNS Censorship", August 2014,
<https://www.usenix.org/system/files/conference/foci14/
foci14-anonymous.pdf>.
[Aryan-2013]
Aryan, S., Aryan, H., and J. A. Halderman, "Internet
Censorship in Iran: A First Look", 2012,
<https://jhalderm.com/pub/papers/iran-foci13.pdf>.
[BBC-2013] BBC News, "Google and Microsoft agree steps to block abuse
images", November 2013,
<http://www.bbc.com/news/uk-24980765>.
[BBC-2013b]
BBC, "China employs two million microblog monitors state
media say", 2013,
<https://www.bbc.com/news/world-asia-china-24396957>.
[Bock-2019]
Bock, K., Hughey, G., Qiang, X., and D. Levin, "Geneva:
Evolving Censorship Evasion Strategies",
DOI 10.1145/3319535.3363189, November 2019,
<https://geneva.cs.umd.edu/papers/geneva_ccs19.pdf>.
[Bock-2020]
Bock, K., Fax, Y., Reese, K., Singh, J., and D. Levin,
"Detecting and Evading Censorship-in-Depth: A Case Study
of Iran's Protocol Filter", January 2020,
<https://geneva.cs.umd.edu/papers/evading-censorship-in-
depth.pdf>.
[Bock-2020b]
Bock, K., iyouport, Anonymous, Merino, L-H., Fifield, D.,
Houmansadr, A., and D. Levin, "Exposing and Circumventing
China's Censorship of ESNI", August 2020,
<https://geneva.cs.umd.edu/posts/china-censors-esni/
esni/>.
[Bock-2021]
Bock, K., Bharadwaj, P., Singh, J., and D. Levin, "Your
Censor is My Censor: Weaponizing Censorship Infrastructure
for Availability Attacks",
DOI 10.1109/SPW53761.2021.00059, May 2021,
<https://geneva.cs.umd.edu/papers/woot21-weaponizing-
availability.pdf>.
[Bock-2021b]
Bock, K., Naval, G., Reese, K., and D. Levin, "Even
Censors Have a Backup: Examining China's Double HTTPS
Censorship Middleboxes", FOCI '21: Proceedings of the ACM
SIGCOMM 2021 Workshop on Free and Open Communications on
the Internet, Pages 1-7, DOI 10.1145/3473604.3474559,
August 2021,
<https://geneva.cs.umd.edu/papers/foci21.pdf>.
[Bortzmeyer-2015]
Bortzmeyer, S., "DNS Censorship (DNS Lies) As Seen By RIPE
Atlas", December 2015,
<https://labs.ripe.net/Members/stephane_bortzmeyer/dns-
censorship-dns-lies-seen-by-atlas-probes>.
[Boyle-1997]
Boyle, J., "Foucault in Cyberspace: Surveillance,
Sovereignty, and Hardwired Censors", 66 University of
Cincinnati Law Review 177-205, 1997,
<https://scholarship.law.duke.edu/
faculty_scholarship/619/>.
[Cao-2016] Cao, Y., Qian, Z., Wang, Z., Dao, T., Krishnamurthy, S.,
and L. Marvel, "Off-Path TCP Exploits: Global Rate Limit
Considered Dangerous", August 2016,
<https://www.usenix.org/system/files/conference/
usenixsecurity16/sec16_paper_cao.pdf>.
[CERT-2000]
CERT, "CERT Advisory CA-1996-21 TCP SYN Flooding and IP
Spoofing Attacks", 2000,
<https://vuls.cert.org/confluence/display/historical/
CERT+Advisory+CA-
1996-21+TCP+SYN+Flooding+and+IP+Spoofing+Attacks>.
[Chai-2019]
Chai, Z., Ghafari, A., and A. Houmansadr, "On the
Importance of Encrypted-SNI (ESNI) to Censorship
Circumvention", 2019,
<https://www.usenix.org/system/files/
foci19-paper_chai_update.pdf>.
[Cheng-2010]
Cheng, J., "Google stops Hong Kong auto-redirect as China
plays hardball", June 2010, <http://arstechnica.com/tech-
policy/2010/06/google-tweaks-china-to-hong-kong-redirect-
same-results/>.
[Cimpanu-2019]
Cimpanu, C., "Russia to disconnect from the internet as
part of a planned test", February 2019,
<https://www.zdnet.com/article/russia-to-disconnect-from-
the-internet-as-part-of-a-planned-test/>.
[CitizenLab-2018]
Marczak, B., Dalek, J., McKune, S., Senft, A., Scott-
Railton, J., and R. Deibert, "Bad Traffic: Sandvine's
PacketLogic Devices Used to Deploy Government Spyware in
Turkey and Redirect Egyptian Users to Affiliate Ads?",
March 2018, <https://citizenlab.ca/2018/03/bad-traffic-
sandvines-packetlogic-devices-deploy-government-spyware-
turkey-syria/>.
[Clayton-2006]
Clayton, R., Murdoch, S.J., and R.N.M. Watson, "Ignoring
the Great Firewall of China", Lecture Notes in Computer
Science, Volume 4258, DOI 10.1007/11957454_2, 2006,
<https://link.springer.com/chapter/10.1007/11957454_2>.
[Condliffe-2013]
Condliffe, J., "Google Announces Massive New Restrictions
on Child Abuse Search Terms", November 2013,
<http://gizmodo.com/google-announces-massive-new-
restrictions-on-child-abus-1466539163>.
[Cowie-2011]
Cowie, J., "Egypt Leaves The Internet", NANOG 51, February
2011,
<https://archive.nanog.org/meetings/nanog51/presentations/
Tuesday/LT-Cowie-Egypt%20Leaves%20The%20Internet.pdf>.
[Crandall-2010]
Park, J.C. and J. Crandall, "Empirical Study of a
National-Scale Distributed Intrusion Detection System:
Backbone-Level Filtering of HTML Responses in China", June
2010, <http://www.cs.unm.edu/~crandall/icdcs2010.pdf>.
[Dada-2017]
Dada, T. and P. Micek, "Launching STOP: the #KeepItOn
internet shutdown tracker", September 2017,
<https://www.accessnow.org/keepiton-shutdown-tracker/>.
[Dalek-2013]
Dalek, J., Haselton, B., Noman, H., Senft, A., Crete-
Nishihata, M., Gill, P., and R. J. Deibert, "A Method for
Identifying and Confirming the Use of URL Filtering
Products for Censorship", IMC '13: Proceedings of the 2013
conference on Internet measurement conference, Pages
23-30, DOI 10.1145/2504730.2504763, October 2013,
<http://conferences.sigcomm.org/imc/2013/papers/imc112s-
dalekA.pdf>.
[Ding-1999]
Ding, C., Chi, C. H., Deng, J., and C. L. Dong,
"Centralized Content-Based Web Filtering and Blocking: How
Far Can It Go?", IEEE SMC'99 Conference Proceedings,
DOI 10.1109/ICSMC.1999.825218, October 1999,
<http://citeseerx.ist.psu.edu/viewdoc/
download?doi=10.1.1.132.3302&rep=rep1&type=pdf>.
[DMLP-512] Digital Media Law Project, "Protecting Yourself Against
Copyright Claims Based on User Content", May 2012,
<https://www.dmlp.org/legal-guide/protecting-yourself-
against-copyright-claims-based-user-content>.
[Dobie-2007]
Dobie, M., "Junta tightens media screw", BBC News,
September 2007,
<http://news.bbc.co.uk/2/hi/asia-pacific/7016238.stm>.
[EC-2012] European Commission, "Summary of the results of the Public
Consultation on the future of electronic commerce in the
Internal Market and the implementation of the Directive on
electronic commerce (2000/31/EC)", January 2012,
<https://ec.europa.eu/information_society/newsroom/image/
document/2017-4/
consultation_summary_report_en_2010_42070.pdf>.
[EC-gambling-2012]
European Commission, "Online gambling in the Internal
Market Accompanying the document Communication from the
Commission to the European Parliament, the Council, the
Economic and Social Committee and the Committee of the
Regions Towards a comprehensive framework for online
gambling", 2012, <https://eur-lex.europa.eu/legal-
content/EN/TXT/?uri=CELEX:52012SC0345>.
[EC-gambling-2019]
European Commission, "Evaluation of regulatory tools for
enforcing online gambling rules and channelling demand
towards controlled offers", January 2019,
<https://ec.europa.eu/growth/content/evaluation-
regulatory-tools-enforcing-online-gambling-rules-and-
channelling-demand-towards-1_en>.
[EFF-2017] Malcom, J., Rossi, G., and M. Stoltz, "Which Internet
registries offer the best protection for domain owners?",
Electronic Frontier Foundation, July 2017,
<https://www.eff.org/files/2017/08/02/
domain_registry_whitepaper.pdf>.
[ekr-2021] Rescorla, E., "Overview of Apple's Client-side CSAM
Scanning", August 2021,
<https://educatedguesswork.org/posts/apple-csam-intro/>.
[Elmenhorst-2021]
Elmenhorst, K., Schuetz, B., Aschenbruck, N., and S.
Basso, "Web Censorship Measurements of HTTP/3 over QUIC",
IMC '21: Proceedings of the 21st ACM Internet Measurement
Conference, Pages 276-282, DOI 10.1145/3487552.3487836,
November 2021,
<https://dl.acm.org/doi/pdf/10.1145/3487552.3487836>.
[Elmenhorst-2022]
Elmenhorst, K., "A Quick Look at QUIC Censorship", April
2022,
<https://www.opentech.fund/news/a-quick-look-at-quic/>.
[Eneman-2010]
Eneman, M., "Internet service provider (ISP) filtering of
child-abusive material: A critical reflection of its
effectiveness", DOI 10.1080/13552601003760014, June 2010,
<https://www.tandfonline.com/doi/
abs/10.1080/13552601003760014>.
[Ensafi-2013]
Ensafi, R., Knockel, J., Alexander, G., and J.R. Crandall,
"Detecting Intentional Packet Drops on the Internet via
TCP/IP Side Channels: Extended Version",
DOI 10.48550/arXiv.1312.5739, December 2013,
<http://arxiv.org/pdf/1312.5739v1.pdf>.
[Fifield-2015]
Fifield, D., Lan, C., Hynes, R., Wegmann, P., and V.
Paxson, "Blocking-resistant communication through domain
fronting", DOI 10.1515/popets-2015-0009, May 2015,
<https://petsymposium.org/2015/papers/03_Fifield.pdf>.
[Gatlan-2019]
Gatlan, S., "South Korea is Censoring the Internet by
Snooping on SNI Traffic", February 2019,
<https://www.bleepingcomputer.com/news/security/south-
korea-is-censoring-the-internet-by-snooping-on-sni-
traffic/>.
[Gilad] Gilad, Y. and A. Herzberg, "Off-Path TCP Injection
Attacks", ACM Transactions on Information and System
Security, Volume 16, Issue 4, Article No.: 13, pp. 1-32,
DOI 10.1145/2597173, April 2014,
<https://doi.org/10.1145/2597173>.
[Glanville-2008]
Glanville, J., "The big business of net censorship", The
Guardian, November 2008,
<http://www.theguardian.com/commentisfree/2008/nov/17/
censorship-internet>.
[Google-2018]
"Google Cloud Networking Incident #18018", November 2018,
<https://status.cloud.google.com/incident/cloud-
networking/18018>.
[Google-RTBF]
Google, Inc., "Search removal request under data
protection law in Europe", 2015,
<https://support.google.com/legal/contact/
lr_eudpa?product=websearch>.
[Grover-2019]
Grover, G., Singh, K., and E. Hickok, Ed., "Reliance Jio
is using SNI inspection to block websites", November 2019,
<https://cis-india.org/internet-governance/blog/reliance-
jio-is-using-sni-inspection-to-block-websites>.
[HADOPI] Hadopi, "Hadopi | Haute Autorité pour la diffusion des
oeuvres et la protection des droits sur internet",
<https://www.hadopi.fr/>.
[Halley-2008]
Halley, B., "How DNS cache poisoning works", October 2008,
<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", OpenNet Initiative, July 2009,
<https://opennet.net/blog/2009/07/china-shuts-down-
internet-xinjiang-region-after-riots>.
[Hepting-2011]
Wikipedia, "Hepting v. AT&T", September 2023,
<https://en.wikipedia.org/wiki/
Hepting_v._AT%26T&oldid=1175143505>.
[Hertel-2015]
Hertel, O., "Comment les autorités peuvent bloquer un site
Internet" [How authorities can block a website], March
2015, <https://www.sciencesetavenir.fr/high-tech/comment-
les-autorites-peuvent-bloquer-un-site-internet_35828>.
[Hjelmvik-2010]
Hjelmvik, E. and W. John, "Breaking and Improving Protocol
Obfuscation", Technical Report No. 2010-05, ISSN
1652-926X, July 2010,
<https://www.iis.se/docs/hjelmvik_breaking.pdf>.
[Husak-2016]
Husák, M., Čermák, M., Jirsík, T., and P. Čeleda, "HTTPS
traffic analysis and client identification using passive
SSL/TLS fingerprinting", DOI 10.1186/s13635-016-0030-7,
February 2016, <https://link.springer.com/article/10.1186/
s13635-016-0030-7>.
[ICANN-2012]
ICANN Security and Stability Advisory Committee, "Guidance
for Preparing Domain Name Orders, Seizures & Takedowns",
January 2012,
<https://www.icann.org/en/system/files/files/guidance-
domain-seizures-07mar12-en.pdf>.
[ICANN-SSAC-2012]
ICANN Security and Stability Advisory Committee (SSAC),
"SAC 056: SSAC Advisory on Impacts of Content Blocking via
the Domain Name System", October 2012,
<https://www.icann.org/en/system/files/files/sac-
056-en.pdf>.
[Jones-2014]
Jones, B., Lee, T-W., Feamster, N., and P. Gill,
"Automated Detection and Fingerprinting of Censorship
Block Pages", IMC '14: Proceedings of the 2014 Conference
on Internet Measurement Conference, Pages 299-304,
DOI 10.1145/2663716.2663722, November 2014,
<http://conferences2.sigcomm.org/imc/2014/papers/
p299.pdf>.
[Khattak-2013]
Khattak, S., Javed, M., Anderson, P.D., and V. Paxson,
"Towards Illuminating a Censorship Monitor's Model to
Facilitate Evasion", August 2013, <http://0b4af6cdc2f0c599
8459-c0245c5c937c5dedcca3f1764ecc9b2f.r43.cf2.rackcdn.com/
12389-foci13-khattak.pdf>.
[Knight-2005]
Knight, W., "Iranian net censorship powered by US
technology", June 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", FOCI '21: Proceedings of the
ACM SIGCOMM 2021 Workshop on Free and Open Communications
on the Internet, Pages 8-15, DOI 10.1145/3473604.3474560,
April 2021,
<https://dl.acm.org/doi/10.1145/3473604.3474560>.
[Kravtsova-2012]
Kravtsova, Y., "Cyberattacks Disrupt Opposition's
Election", The Moscow Times, October 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", COMPASS '19: Proceedings of the
2nd ACM SIGCAS Conference on Computing and Sustainable
Societies, pages 184-194, DOI 10.1145/3314344.3332502,
July 2019, <https://doi.org/10.1145/3314344.3332502>.
[Li-2017] Li, F., Razaghpanah, A., Molavi Kakhki, A., Akhavan Niaki,
A., Choffnes, D., Gill, P., and A. Mislove, "lib•erate,
(n): a library for exposing (traffic-classification) rules
and avoiding them efficiently",
DOI 10.1145/3131365.3131376, November 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", October 2019,
<https://techcrunch.com/2019/10/30/github-removes-tsunami-
democratics-apk-after-a-takedown-order-from-spain/>.
[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"",
August 2015,
<https://www.usenix.org/system/files/conference/foci15/
foci15-paper-marczak.pdf>.
[Muncaster-2013]
Muncaster, P., "Malaysian election sparks web blocking/
DDoS claims", The Register, May 2013,
<http://www.theregister.co.uk/2013/05/09/
malaysia_fraud_elections_ddos_web_blocking/>.
[Murdoch-2008]
Murdoch, S. J. and R. Anderson, "Tools and Technology of
Internet Filtering" in "Access Denied: The Practice and
Policy of Global Internet Filtering",
DOI 10.7551/mitpress/7617.003.0006, 2008,
<https://doi.org/10.7551/mitpress/7617.003.0006>.
[NA-SK-2019]
Morgus, R., Sherman, J., and S. Nam, "Analysis: South
Korea's New Tool for Filtering Illegal Internet Content",
March 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",
August 2013, <http://0b4af6cdc2f0c5998459-c0245c5c937c5ded
cca3f1764ecc9b2f.r43.cf2.rackcdn.com/12387-foci13-nabi.pdf
>.
[NBC-2014] NBC News, "Exclusive: Snowden Docs Show UK Spies Attacked
Anonymous, Hackers", February 2014,
<http://www.nbcnews.com/feature/edward-snowden-interview/
exclusive-snowden-docs-show-uk-spies-attacked-anonymous-
hackers-n21361>.
[Netsec-2011]
n3t2.3c, "TCP-RST Injection", October 2011,
<https://nets.ec/TCP-RST_Injection>.
[OONI-2018]
Evdokimov, L., "Iran Protests: DPI blocking of Instagram
(Part 2)", February 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", May 2019,
<https://ooni.org/post/2019-china-wikipedia-blocking/>.
[Orion-2013]
Orion, E., "Zimbabwe election hit by hacking and DDoS
attacks", Wayback Machine archive, August 2013, <https://w
eb.archive.org/web/20130825010947/http://www.theinquirer.n
et/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?", Proceedings of the Applied Networking Research
Workshop, Pages 45-51, DOI 10.1145/3340301.3341133, July
2019, <https://irtf.org/anrw/2019/
anrw2019-final44-acmpaginated.pdf>.
[Porter-2005]
Porter, T., "The Perils of Deep Packet Inspection", 2010,
<http://www.symantec.com/connect/articles/perils-deep-
packet-inspection>.
[Rambert-2021]
Rampert, R., Weinberg, Z., Barradas, D., and N. Christin,
"Chinese Wall or Swiss Cheese? Keyword filtering in the
Great Firewall of China", DOI 10.1145/3442381.3450076,
April 2021,
<https://www.andrew.cmu.edu/user/nicolasc/publications/
Rambert-WWW21.pdf>.
[Reda-2017]
Reda, F., "New EU law prescribes website blocking in the
name of "consumer protection"", November 2017,
<https://felixreda.eu/2017/11/eu-website-blocking/>.
[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>.
[RFC8744] Huitema, C., "Issues and Requirements for Server Name
Identification (SNI) Encryption in TLS", RFC 8744,
DOI 10.17487/RFC8744, July 2020,
<https://www.rfc-editor.org/info/rfc8744>.
[RFC9000] Iyengar, J., Ed. and M. Thomson, Ed., "QUIC: A UDP-Based
Multiplexed and Secure Transport", RFC 9000,
DOI 10.17487/RFC9000, May 2021,
<https://www.rfc-editor.org/info/rfc9000>.
[RFC9293] Eddy, W., Ed., "Transmission Control Protocol (TCP)",
STD 7, RFC 9293, DOI 10.17487/RFC9293, August 2022,
<https://www.rfc-editor.org/info/rfc9293>.
[Rushe-2014]
Rushe, D., "Bing censoring Chinese language search results
for users in the US", The Guardian, February 2014,
<http://www.theguardian.com/technology/2014/feb/11/bing-
censors-chinese-language-search-results>.
[RWB-2020] Reporters Without Borders (RSF), "2020 World Press Freedom
Index: 'Entering a decisive decade for journalism,
exacerbated by coronavirus'", April 2020,
<https://rsf.org/en/2020-world-press-freedom-index-
entering-decisive-decade-journalism-exacerbated-
coronavirus>.
[Sandvine-2015]
Sandvine, "Internet Traffic Classification: A Sandvine
Technology Showcase", 2015,
<https://www.researchgate.net/profile/Nirmala-Svsg/post/
Anybody-working-on-Internet-traffic-
classification/attachment/59d63a5779197b807799782d/
AS%3A405810988503040%401473764287142/download/traffic-
classification-identifying-and-measuring-internet-
traffic.pdf>.
[Satija-2021]
Satija, S. and R. Chatterjee, "BlindTLS: Circumventing
TLS-based HTTPS censorship", FOCI '21: Proceedings of the
ACM SIGCOMM 2021 Workshop on Free and Open Communications
on the Internet, Pages 43-49, DOI 10.1145/3473604.3474564,
August 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", October 2007,
<https://www.eff.org/deeplinks/2007/10/eff-tests-agree-ap-
comcast-forging-packets-to-interfere>.
[Senft-2013]
, Crete-Nishihata, M., Dalek, J., Hardy, S., Hilts, A.,
Kleemola, K., Ng, J., Poetranto, I., Senft, A., Sinpeng,
A., Sonne, B., and G. Wiseman, "Asia Chats: Analyzing
Information Controls and Privacy in Asian Messaging
Applications", November 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", May
2015, <https://hal.inria.fr/hal-01202712/document>.
[Siddiqui-2022]
Siddiqui, A., "Lesson Learned: Twitter Shored Up Its
Routing Security", March 2022,
<https://www.manrs.org/2022/03/lesson-learned-twitter-
shored-up-its-routing-security/>.
[SIDN-2020]
Moura, G., "Detecting and Taking Down Fraudulent Webshops
at the .nl ccTLD", February 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", DOI 10.48550/arXiv.1912.08590, December 2019,
<https://arxiv.org/abs/1912.08590>.
[Sophos-2023]
Sophos, "Sophos Firewall: Web filtering basics", 2023,
<https://support.sophos.com/support/s/article/KB-
000036518?language=en_US>.
[SSAC-109-2020]
ICANN Security and Stability Advisory Committee (SSAC),
"SAC109: The Implications of DNS over HTTPS and DNS over
TLS", March 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", December 2016,
<https://www.cs.tufts.edu/comp/116/archive/fall2016/
ctang.pdf>.
[Thomson-2012]
Thomson, I., "Syria cuts off internet and mobile
communication", The Register, November 2012,
<http://www.theregister.co.uk/2012/11/29/
syria_internet_blackout/>.
[TLS-ESNI] Rescorla, E., Oku, K., Sullivan, N., and C. A. Wood, "TLS
Encrypted Client Hello", Work in Progress, Internet-Draft,
draft-ietf-tls-esni-17, 9 October 2023,
<https://datatracker.ietf.org/doc/html/draft-ietf-tls-
esni-17>.
[Tor-2019] Tor, "Tor: Pluggable Transports", 2019,
<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, and V. Paxson, "SoK:
Towards Grounding Censorship Circumvention in Empiricism",
DOI 10.1109/SP.2016.59, May 2016,
<https://oaklandsok.github.io/papers/tschantz2016.pdf>.
[Van-der-Sar-2007]
Van der Sar, E., "How To Bypass Comcast's BitTorrent
Throttling", October 2012, <https://torrentfreak.com/how-
to-bypass-comcast-bittorrent-throttling-071021>.
[Verkamp-2012]
Verkamp, J. P. and M. Gupta, "Inferring Mechanics of Web
Censorship Around the World", August 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", The New York Times,
October 2019,
<https://www.nytimes.com/2019/10/09/world/asia/blizzard-
hearthstone-hong-kong.html>.
[Villeneuve-2011]
Villeneuve, N. and M. Crete-Nishihata, "Open Access:
Chapter 8, Control and Resistance, Attacks on Burmese
Opposition Media", January 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", August 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'", Global Voices Advocacy, 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", NBC News, May 2013,
<https://www.nbcnews.com/tech/tech-news/malaysia-online-
election-battles-take-nasty-turn-flna6c9783842>.
[Wang-2017]
Wang, Z., Cao, Y., Qian, Z., Song, C., and S.V.
Krishnamurthy, "Your State is Not Mine: A Closer Look at
Evading Stateful Internet Censorship",
DOI 10.1145/3131365.3131374, November 2017,
<https://www.cs.ucr.edu/~zhiyunq/pub/
imc17_censorship_tcp.pdf>.
[Wang-2020]
Wang, Z., Zhu, S., Cao, Y., Qian, Z., Song, C.,
Krishnamurthy, S.V., Chan, K.S., and T.D. Braun, "SYMTCP:
Eluding Stateful Deep Packet Inspection with Automated
Discrepancy Discovery", DOI 10.14722/ndss.2020.24083,
February 2020,
<https://www.cs.ucr.edu/~zhiyunq/pub/ndss20_symtcp.pdf>.
[Weaver-2009]
Weaver, N., Sommer, R., and V. Paxson, "Detecting Forged
TCP Reset Packets", September 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", March 2013,
<http://www.zdnet.com/1168-keywords-skype-uses-to-censor-
monitor-its-chinese-users-7000012328/>.
[Wikip-DoS]
Wikipedia, "Denial-of-service attack", March 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", The
Tor Project, July 2012, <https://blog.torproject.org/blog/
knock-knock-knockin-bridges-doors>.
[Winter-2012]
Winter, P. and S. Lindskog, "How China Is Blocking Tor",
April 2012, <http://arxiv.org/pdf/1204.0447v1.pdf>.
[WP-Def-2020]
Wikipedia, "Censorship", March 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", DOI 10.14763/2013.2.122, April 2013,
<https://policyreview.info/articles/analysis/internet-
filtering-trends-liberal-democracies-french-and-german-
regulatory-debates>.
[Zhu-2011] Zhu, T., Bronk, C., and D.S. Wallach, "An Analysis of
Chinese Search Engine Filtering",
DOI 10.48550/arXiv.1107.3794, July 2011,
<http://arxiv.org/ftp/arxiv/papers/1107/1107.3794.pdf>.
[Zmijewski-2014]
Zmijewski, E., "Turkish Internet Censorship Takes a New
Turn", Wayback Machine archive, March 2014,
<http://web.archive.org/web/20200726222723/
https://blogs.oracle.com/internetintelligence/turkish-
internet-censorship-takes-a-new-turn>.
Acknowledgments
This document benefited from discussions with and input from David
Belson, Stéphane Bortzmeyer, Vinicius Fortuna, Gurshabad Grover,
Andrew McConachie, Martin Nilsson, Michael Richardson, Patrick Vacek,
and Chris Wood.
Coauthor Hall performed work on this document before employment at
the Internet Society, and his affiliation listed in this document is
for identification purposes only.
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