Internet DRAFT - draft-irtf-pearg-censorship
draft-irtf-pearg-censorship
pearg J. L. Hall
Internet-Draft Internet Society
Intended status: Informational M. D. Aaron
Expires: 30 September 2023 CU Boulder
A. Andersdotter
B. Jones
N. Feamster
U Chicago
M. Knodel
Center for Democracy & Technology
29 March 2023
A Survey of Worldwide Censorship Techniques
draft-irtf-pearg-censorship-10
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
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This Internet-Draft will expire on 30 September 2023.
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Copyright Notice
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Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 3
2. Terminology . . . . . . . . . . . . . . . . . . . . . . . . . 3
3. Technical Prescription . . . . . . . . . . . . . . . . . . . 4
4. Technical Identification . . . . . . . . . . . . . . . . . . 5
4.1. Points of Control . . . . . . . . . . . . . . . . . . . . 5
4.2. Application Layer . . . . . . . . . . . . . . . . . . . . 7
4.2.1. HTTP Request Header Identification . . . . . . . . . 7
4.2.2. HTTP Response Header Identification . . . . . . . . . 8
4.2.3. Transport Layer Security (TLS) . . . . . . . . . . . 9
4.2.4. Instrumenting Content Distributors . . . . . . . . . 11
4.2.5. DPI Identification . . . . . . . . . . . . . . . . . 13
4.3. Transport Layer . . . . . . . . . . . . . . . . . . . . . 14
4.3.1. Shallow Packet Inspection and Transport Header
Identification . . . . . . . . . . . . . . . . . . . 15
4.3.2. Protocol Identification . . . . . . . . . . . . . . . 16
4.4. Residual Censorship . . . . . . . . . . . . . . . . . . . 17
5. Technical Interference . . . . . . . . . . . . . . . . . . . 18
5.1. Application Layer . . . . . . . . . . . . . . . . . . . . 18
5.1.1. DNS Interference . . . . . . . . . . . . . . . . . . 18
5.2. Transport Layer . . . . . . . . . . . . . . . . . . . . . 20
5.2.1. Performance Degradation . . . . . . . . . . . . . . . 20
5.2.2. Packet Dropping . . . . . . . . . . . . . . . . . . . 21
5.2.3. RST Packet Injection . . . . . . . . . . . . . . . . 22
5.3. Routing Layer . . . . . . . . . . . . . . . . . . . . . . 23
5.3.1. Network Disconnection . . . . . . . . . . . . . . . . 23
5.3.2. Adversarial Route Announcement . . . . . . . . . . . 24
5.4. Multi-layer and Non-layer . . . . . . . . . . . . . . . . 25
5.4.1. Distributed Denial of Service (DDoS) . . . . . . . . 25
5.4.2. Censorship in Depth . . . . . . . . . . . . . . . . . 26
6. Non-Technical Interference . . . . . . . . . . . . . . . . . 26
6.1. Manual Filtering . . . . . . . . . . . . . . . . . . . . 26
6.2. Self-Censorship . . . . . . . . . . . . . . . . . . . . . 27
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6.3. Server Takedown . . . . . . . . . . . . . . . . . . . . . 27
6.4. Notice and Takedown . . . . . . . . . . . . . . . . . . . 27
6.5. Domain-Name Seizures . . . . . . . . . . . . . . . . . . 27
7. Future work . . . . . . . . . . . . . . . . . . . . . . . . . 28
8. Contributors . . . . . . . . . . . . . . . . . . . . . . . . 28
9. Informative References . . . . . . . . . . . . . . . . . . . 28
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 45
1. Introduction
Censorship is where an entity in a position of power -- such as a
government, organization, or individual -- suppresses communication
that it considers objectionable, harmful, sensitive, politically
incorrect or inconvenient [WP-Def-2020]. Although censors that
engage in censorship must do so through legal, military, or other
means, this document focuses largely on technical mechanisms used to
achieve network censorship.
This document describes technical mechanisms that censorship regimes
around the world use for blocking or impairing Internet traffic. See
[RFC7754] for a discussion of Internet blocking and filtering in
terms of implications for Internet architecture, rather than end-user
access to content and services. There is also a growing field of
academic study of censorship circumvention (see the review article of
[Tschantz-2016]), results from which we seek to make relevant here
for protocol designers and implementers.
Censorship circumvention also impacts the cost of implementation of a
censorship measure and we include mentions of tradeoffs in relation
to such costs in conjunction with each technical method identified
below.
This document has seen extensive discussion and review in the IRTF
Privacy Enhancement and Assessment Research Group (PEARG) and
represents the consensus of that group. It is not an IETF product
and is not a standard.
2. Terminology
We describe three elements of Internet censorship: prescription,
identification, and interference. The document contains three major
sections, each corresponding to one of these elements. Prescription
is the process by which censors determine what types of material they
should censor, e.g., classifying pornographic websites as
undesirable. Identification is the process by which censors classify
specific traffic or traffic identifiers to be blocked or impaired,
e.g., deciding that webpages containing "sex" in an HTTP (Hypertext
Transport Protocol) Header or that accept traffic through the URL
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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
[SIDN2020].
There are typically a few types of blocklist elements: Keyword,
domain name, protocol, or Internet Protocol (IP) address. Keyword
and domain name blocking take place at the application level, e.g.,
HTTP; protocol blocking often occurs using deep packet inspection to
identify a forbidden protocol; IP blocking tends to take place using
IP addresses in IPv4/IPv6 headers. Some censors also use the
presence of certain keywords to enable more aggressive blocklists
[Rambert-2021] or to be more permissive with content [Knockel-2021].
The mechanisms for building up these blocklists vary. Censors can
purchase from private industry "content control" software, which lets
censors filter traffic from broad categories they would like to
block, such as gambling or pornography [Knight-2005]. In these
cases, these private services attempt to categorize every semi-
questionable website to allow for meta-tag blocking. Similarly, they
tune real-time content heuristic systems to map their assessments
onto categories of objectionable content.
Countries that are more interested in retaining specific political
control typically have ministries or organizations that maintain
blocklists. Examples include the Ministry of Industry and
Information Technology in China, Ministry of Culture and Islamic
Guidance in Iran, and specific to copyright in France [HADOPI-2020]
and across the EU for consumer protection law [Reda-2017].
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Content-layer filtering of images and video 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 eco-system (e.g., domain name system or certificate
authorities) or on the end-client side (e.g., in an end-user device
such as a smartphone, laptop or desktop or software executed on such
devices). An important aspect of pervasive technical interception is
the necessity to rely on software or hardware to intercept the
content the censor is interested in. There are various logical and
physical points-of-control censors may use for interception
mechanisms, including, though not limited to, the following:
* Internet Backbone: If a censor controls elements of Internet
network infrastructure, such as the international gateways into a
region or Internet exchange points, those chokepoints 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 chokepoints and points of
control [Leyba-2019].
* Internet Service Providers: Internet Service Providers are
frequently exploited points of control. They have the benefit of
being easily enumerable by a censor -- often falling under the
jurisdictional or operational control of a censor in an
indisputable way -- with the additional feature that an ISP can
identify the regional and international traffic of all their
users. The censor's filtration mechanisms can be placed on an ISP
via governmental mandates, ownership, or voluntary/coercive
influence.
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* Institutions: Private institutions such as corporations, schools,
and Internet cafes can use filtration mechanisms. These
mechanisms are occasionally at the request of a government censor,
but can also be implemented to help achieve institutional goals,
such as fostering a particular moral outlook on life by school-
children, independent of broader society or government goals.
* Content Distribution Network (CDN): CDNs seek to collapse network
topology in order to better locate content closer to the service's
users. This reduces content transmission latency and improves
quality of service. The CDN service's content servers, located
"close" to the user in a network-sense, can be powerful points of
control for censors, especially if the location of CDN
repositories allow for easier interference.
* Certificate Authorities (CAs) for Public-Key Infrastructures
(PKIs): Authorities that issue cryptographically secured resources
can be a significant point of control. CAs that issue
certificates to domain holders for TLS/HTTPS (the Web PKI) or
Regional/Local Internet Registries (RIRs) that issue Route
Origination Authorizations (ROAs) to BGP operators can be forced
to issue rogue certificates that may allow compromise, i.e., by
allowing censorship software to engage in identification and
interference where it may not have been possible before. CAs may
also be forced to revoke certificates. This may lead to
adversarial traffic routing or TLS interception being allowed, or
an otherwise rightful origin or destination point of traffic flows
being unable to communicate in a secure way.
* Services: Application service providers can be pressured, coerced,
or legally required to censor specific content or data flows.
Service providers naturally face incentives to maximize their
potential customer base, and potential service shutdowns or legal
liability due to censorship efforts may seem much less attractive
than potentially excluding content, users, or uses of their
service. Services have increasingly become focal points of
censorship discussions, as well as the focus of discussions of
moral imperatives to use censorship tools.
* Content sites: On the service side of communications lie many
platforms that publish user-generated content 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.
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* Personal Devices: Censors can mandate censorship software be
installed on the device level. This has many disadvantages in
terms of scalability, ease-of-circumvention, and operating system
requirements. (Of course, if a personal device is treated with
censorship software before sale and this software is difficult to
reconfigure, this may work in favor of those seeking to control
information, say for children, students, customers, or employees.)
The emergence of mobile devices has exacerbate these feasibility
problems. This software can also be mandated by institutional
actors acting on non-governmentally mandated moral imperatives.
At all levels of the network hierarchy, the filtration mechanisms
used to censor undesirable traffic are essentially the same: a censor
either directly identifies undesirable content using the identifiers
described below and then uses a blocking or shaping mechanism such as
the ones exemplified below to prevent or impair access, or requests
that an actor ancillary to the censor, such as a private entity,
perform these functions. Identification of undesirable traffic can
occur at the application, transport, or network layer of the IP
stack. Censors often focus on web traffic, so the relevant protocols
tend to be filtered in predictable ways (see Section 4.2.1 and
Section 4.2.2). For example, a subversive image might make it past a
keyword filter. However, if later the image is deemed undesirable, a
censor may then blocklist the provider site's IP address.
4.2. Application Layer
The following subsections describe properties and tradeoffs of common
ways in which censors filter using application-layer information.
Each subsection includes empirical examples describing these common
behaviors for further reference.
4.2.1. HTTP Request Header Identification
An HTTP header contains a lot of useful information for traffic
identification. Although "host" is the only required field in an
HTTP request header (for HTTP/1.1 and later), an HTTP method field is
necessary to do anything useful. As such, "method" and "host" are
the two fields used most often for ubiquitous censorship. A censor
can sniff traffic and identify a specific domain name (host) and
usually a page name (GET /page) as well. This identification
technique is usually paired with transport header identification (see
Section 4.3.1) for a more robust method.
Tradeoffs: Request Identification is a technically straight-forward
identification method that can be easily implemented at the Backbone
or ISP level. The hardware needed for this sort of identification is
cheap and easy-to-acquire, making it desirable when budget and scope
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are a concern. HTTPS (Hyptertext 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/ URL filtering in many countries,
including Bangladesh, Bahrain, China, India, Iran, Malaysia,
Pakistan, Russia, Saudi Arabia, South Korea, Thailand, and Turkey
[Verkamp-2012] [Nabi-2013] [Aryan-2012]. Commercial technologies are
often purchased by censors [Dalek-2013]. These commercial
technologies use a combination of HTTP Request Identification and
Transport Header Identification to filter specific URLs. Dalek et
al. and Jones et al. identified the use of these products in the wild
[Dalek-2013] [Jones-2014].
4.2.2. HTTP Response Header Identification
While HTTP Request Header Identification relies on the information
contained in the HTTP request from client to server, response
identification uses information sent in response by the server to
client to identify undesirable content.
Tradeoffs: As with HTTP Request Header Identification, the techniques
used to identify HTTP traffic are well-known, cheap, and relatively
easy to implement. However, they are made useless by HTTPS because
HTTPS encrypts the response and its headers.
The response fields are also less helpful for identifying content
than request fields, as "Server" could easily be identified using
HTTP Request Header identification, and "Via" is rarely relevant.
HTTP Response censorship mechanisms normally let the first n packets
through while the mirrored traffic is being processed; this may allow
some content through and the user may be able to detect that the
censor is actively interfering with undesirable content.
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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 Transport Layer Security (TLS) (and by extension
HTTPS). Most of these techniques relate to the Server Name
Indication (SNI) field, including censoring SNI, Encrypted SNI, or
omitted SNI. Censors can also censor HTTPS content via server
certificates. Note that TLS 1.3 acts as a security component of
QUIC.
4.2.3.1. Server Name Indication (SNI)
In encrypted connections using TLS, there may be servers that host
multiple "virtual servers" at a given network address, and the client
will need to specify in the Client Hello message which domain name it
seeks to connect to (so that the server can respond with the
appropriate TLS certificate) using the Server Name Indication (SNI)
TLS extension [RFC6066]. The Client Hello message is unencrypted for
TCP-based TLS. When using QUIC, the Client Hello message is
encrypted but its confidentiality is not effectively protected
because the initial encryption keys are derived using a value that is
visible on the wire. Since SNI is often sent in the clear (as are
the cert fields sent in response), censors and filtering software can
use it (and response cert fields) as a basis for blocking, filtering,
or impairment by dropping connections to domains that match
prohibited content (e.g., bad.foo.example may be censored while
good.foo.example is not) [Shbair-2015]. There are ongoing
standardization efforts in the TLS Working Group to encrypt SNI
[I-D.ietf-tls-sni-encryption] [I-D.ietf-tls-esni] and recent research
shows promising results in the use of encrypted SNI in the face of
SNI-based filtering [Chai-2019] in some countries.
Domain fronting has been one popular way to avoid identification by
censors [Fifield-2015]. To avoid identification by censors,
applications using domain fronting put a different domain name in the
SNI extension than in the Host: header, which is protected by HTTPS.
The visible SNI would indicate an unblocked domain, while the blocked
domain remains hidden in the encrypted application header. Some
encrypted messaging services relied on domain fronting to enable
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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.
Tradeoffs: Some clients do not send the SNI extension (e.g., clients
that only support versions of SSL and not TLS), rendering this method
ineffective (see Section 4.2.3.3). In addition, this technique
requires deep packet inspection (DPI) techniques that can be
computationally and infrastructurally expensive, especially when
applied to QUIC where DPI requires key extraction and decryption of
the Client Hello in order to read the SNI. Improper configuration of
an SNI-based block can result in significant overblocking, e.g., when
a second-level domain like populardomain.example is inadvertently
blocked. In the case of encrypted SNI, pressure to censor may
transfer to other points of intervention, such as content and
application providers.
Empirical Examples: There are many examples of security firms that
offer SNI-based filtering products [Trustwave-2015] [Sophos-2015]
[Shbair-2015], and the governments of China, Egypt, Iran, Qatar,
South Korea, Turkey, Turkmenistan, and the UAE all do widespread SNI
filtering or blocking [OONI-2018] [OONI-2019] [NA-SK-2019]
[CitizenLab-2018] [Gatlan-2019] [Chai-2019] [Grover-2019]
[Singh-2019]. SNI blocking against QUIC traffic 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 Encrypted SNI (ESNI) extension
is available to prevent the data leakage caused by SNI, which
encrypts only the SNI field. Unfortunately, censors can target
connections that use the ESNI extension specifically for censorship.
This guarantees overblocking for the censor, but can be worth the
cost if ESNI is not yet widely deployed within the country.
Encrypted Client Hello (ECH) is the emerging standard for protecting
the entire TLS Client Hello, but it is not yet widely deployed.
Tradeoffs: The cost to censoring Encrypted SNI (ESNI) is
significantly higher than SNI to a censor, as the censor can no
longer target censorship to specific domains and guarantees over-
blocking. In these cases, the censor uses the over-blocking to
discourage the use of ESNI entirely.
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Empirical Examples: In 2020, China began censoring all uses of
Encrypted ESNI (ESNI) [Bock-2020b], even for innocuous connections.
The censorship mechanism for China's ESNI censorship differs from how
China censors SNI-based connections, suggesting that new middleboxes
were deployed specifically to target ESNI connections.
4.2.3.3. Omitted-SNI
Researchers have observed that some clients omit the SNI extension
entirely. This omitted-SNI approach limits the information available
to a censor. Like with ESNI, censors can choose to block connections
that omit the SNI, though this too risks over-blocking.
Tradeoffs: The approach of censoring all connections that omit the
SNI field is guaranteed to over-block, though connections that omit
the SNI field should be relatively rare in the wild.
Empirical Examples: In the past, researchers have observed censors in
Russia blocking connections that omit the SNI field [Bock-2020b].
4.2.3.4. Server Response Certificate
During the TLS handshake after the TLS Client Hello, the server will
respond with the TLS certificate. This certificate also contains the
domain the client is trying to access, creating another avenue that
censors can use to perform censorship. This technique will not work
in TLS 1.3, as the certificate will be encrypted.
Tradeoffs: Censoring based on the server certificate requires DPI
techniques that can be more computationally expensive compared to
other methods. Additionally, the certificate is sent later in the
TLS Handshake compared to the SNI field, forcing the censor to track
the connection longer.
Empirical Examples: Researchers have observed the Reliance Jio ISP in
India using certificate response fields to censor connections
[Satija-2021].
4.2.4. Instrumenting Content Distributors
Many governments pressure content providers to censor themselves, or
provide the legal framework within which content distributors are
incentivized to follow the content restriction preferences of agents
external to the content distributor [Boyle-1997]. Due to the
extensive reach of such censorship, we define content distributor as
any service that provides utility to users, including everything from
web sites to storage to locally installed programs.
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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 on images and
videos known to be restricted either by governments, institutions,
organizations or the distributor themselves [ekr-2021].
A different method of instrumenting content distributors consists of
requiring a distributor to disassociate with some categories of
users. See also Section 6.4.
Tradeoffs: By instrumenting content distributors to identify
restricted content or content providers, the censor can gain new
information at the cost of political capital with the companies it
forces or encourages to participate in censorship. For example, the
censor can gain insight about the content of encrypted traffic by
coercing web sites to identify restricted content. Coercing content
distributors to regulate users, categories of users, content and
content providers may encourage users and content providers to
exhibit self-censorship, an additional advantage for censors (see
Section 6.2). The tradeoffs for instrumenting content distributors
are highly dependent on the content provider and the requested
assistance. A typical concern is that the targeted keywords or
categories of users are too broad, risk being too broadly applied, or
are not subjected to a sufficiently robust legal process prior to
their mandatory application (see p. 8 of [EC-2012]).
Empirical Examples: Researchers discovered keyword identification by
content providers on platforms ranging from instant messaging
applications [Senft-2013] to search engines [Rushe-2015] [Cheng-2010]
[Whittaker-2013] [BBC-2013] [Condliffe-2013]. To demonstrate the
prevalence of this type of keyword identification, we look to search
engine censorship.
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]
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[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 US law, requires
modification of search engine results in response to either
copyright, trademark, data protection or defamation concerns
[EC-2012].
Depending on the output, search engine keyword identification may be
difficult or easy to detect. In some cases, specialized or blank
results provide a trivial enumeration mechanism, but more subtle
censorship can be difficult to detect. In February 2015, Microsoft's
search engine, Bing, was accused of censoring Chinese content outside
of China [Rushe-2015] because Bing returned different results for
censored terms in Chinese and English. However, it is possible that
censorship of the largest base of Chinese search users, China, biased
Bing's results so that the more popular results in China (the
uncensored results) were also more popular for Chinese speakers
outside of China.
Disassociation by content distributors from certain categories of
users has happened for instance in Spain, as a result of the conflict
between the 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 (deep packet inspection) technically is any kind of packet
analysis beyond IP address and port number and has become
computationally feasible as a component of censorship mechanisms in
recent years [Wagner-2009]. Unlike other techniques, DPI reassembles
network flows to examine the application "data" section, as opposed
to only headers, and is therefore often used for keyword
identification. DPI also differs from other identification
technologies because it can leverage additional packet and flow
characteristics, e.g., packet sizes and timings, when identifying
content. To prevent substantial quality of service (QoS) impacts,
DPI normally analyzes a copy of data while the original packets
continue to be routed. Typically, the traffic is split using either
a mirror switch or fiber splitter, and analyzed on a cluster of
machines running Intrusion Detection Systems (IDS) configured for
censorship.
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Tradeoffs: DPI is one of the most expensive identification mechanisms
and can have a large QoS impact [Porter-2010]. When used as a
keyword filter for TCP flows, DPI systems can cause also major
overblocking problems. Like other techniques, DPI is less useful
against encrypted data, though DPI can leverage unencrypted elements
of an encrypted data flow, e.g., the Server Name Indication (SNI)
sent in the clear for TLS, or metadata about an encrypted flow, e.g.,
packet sizes, which differ across video and textual flows, to
identify traffic. See Section 4.2.3.1 for more information about
SNI-based filtration mechanisms.
Other kinds of information can be inferred by comparing certain
unencrypted elements exchanged during TLS handshakes to similar data
points from known sources. This practice, called TLS fingerprinting,
allows a probabilistic identification of a party's operating system,
browser, or application, based on a comparison of the specific
combinations of TLS version, ciphersuites, compression options, etc.
sent in the ClientHello message to similar signatures found in
unencrypted traffic [Husak-2016].
Despite these problems, DPI is the most powerful identification
method and is widely used in practice. The Great Firewall of China
(GFW), the largest censorship system in the world, uses DPI to
identify restricted content over HTTP and DNS and 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 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
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4.3.1. Shallow Packet Inspection and Transport Header Identification
Of the various shallow packet inspection methods, Transport Header
Identification is the most pervasive, reliable, and predictable type
of identification. Transport headers contain a few invaluable pieces
of information that must be transparent for traffic to be
successfully routed: destination and source IP address and port.
Destination and Source IP are doubly useful, as not only does it
allow a censor to block undesirable content via IP blocklisting, but
also allows a censor to identify the IP of the user making the
request and the IP address of the destination being visited, which in
most cases can be used to infer the domain being visited
[Patil-2019]. Port is useful for allowlisting certain applications.
Combining IP address, port and protocol information found in the
transport header, shallow packet inspection can be used by a censor
to identify specific TCP or UDP endpoints. UDP endpoint blocking has
been observed in the context of QUIC blocking [Elmenhorst-2021].
Trade offs: header identification is popular due to its simplicity,
availability, and robustness.
Header identification is trivial to implement, but is difficult to
implement in backbone or ISP routers at scale, and is therefore
typically implemented with DPI. Blocklisting an IP is equivalent to
installing a specific route on a router (such as a /32 route for IPv4
addresses and a /128 route for IPv6 addresses). However, due to
limited flow table space, this cannot scale beyond a few thousand IPs
at most. IP blocking is also relatively crude. It often leads to
overblocking and cannot deal with some services like content
distribution networks (CDN) that host content at hundreds or
thousands of IP addresses. Despite these limitations, IP blocking is
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
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fall back to HTTP. A counter-example 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-2012]. A simple protocol identification would be
to recognize all TCP traffic over port 443 as HTTPS, but more
sophisticated analysis of the statistical properties of payload data
and flow behavior, would be more effective, even when port 443 is not
used [Hjelmvik-2010] [Sandvine-2014].
If censors can detect circumvention tools, they can block them, so
censors like China are extremely interested in identifying the
protocols for censorship circumvention tools. In recent years, this
has devolved into an 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 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
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lead to over-blocking if the allowed lists of protocols is too small
or incomplete, but can be cheap to implement, as many standard
'allowed' protocols are simple to identify (such as HTTP).
Empirical Examples: Protocol identification can be easy to detect if
it is conducted in real time and only a particular protocol is
blocked, but some types of protocol identification, like active
scanning, are much more difficult to detect. Protocol identification
has been used by Iran to identify and throttle SSH traffic to make it
unusable [Anonymous-2007] and by China to identify and block Tor
relays [Winter-2012]. Protocol identification has also been used for
traffic management, such as the 2007 case where Comcast in the United
States used RST injection (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+port), or
4-tuple (client IP+port, server IP+port). Future connections that
match the tuple of information the censor records will be disrupted
[Bock-2021].
Residual censorship can sometimes be difficult to identify and can
often complicate censorship measurement.
Trade offs: The impact of residual censorship is to provide users
with further discouragement from trying to access forbidden content,
though it is not clear how successful it is at accomplishing this.
Empirical Examples: China has used 3-tuple residual censorship in
conjunction with their HTTP censorship for years and researchers have
reported seeing similar residual censorship for HTTPS. China seems
to use a mix of 3-tuple and 4-tuple residual censorship for their
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censorship of HTTPS with ESNI. Some censors that perform censorship
via packet dropping often accidentally implement 4-tuple residual
censorship, including Iran and Kazakhstan [Bock-2021].
5. Technical Interference
5.1. Application Layer
5.1.1. DNS Interference
There are a variety of mechanisms that censors can use to block or
filter access to content by altering responses from the DNS
[AFNIC-2013] [ICANN-SSAC-2012], including blocking the response,
replying with an error message, or responding with an incorrect
address. Note that there are now encrypted transports for DNS
queries in DNS-over-HTTPS [RFC8484] and DNS-over-TLS [RFC7858] that
can mitigate interference with DNS queries between the stub and the
resolver.
Responding to a DNS query with an incorrect address can be achieved
with on-path interception, off-path cache poisoning, and lying by the
nameserver.
"DNS mangling" is a network-level technique of on-path interception
where an incorrect IP address is returned in response to a DNS query
to a censored destination. Some Chinese networks, for example, do
this (we are not aware of any other wide-scale uses of mangling). On
those Chinese networks, every DNS request in transit is examined
(presumably by network inspection technologies such as DPI) and, if
it matches a censored domain, a false response is injected. End
users can see this technique in action by simply sending DNS requests
to any unused IP address in China (see example below). If it is not
a censored name, there will be no response. If it is censored, a
forged response will be returned. For example, using the command-
line dig utility to query an unused IP address in China of 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
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the authoritative name server can respond with an alternative IP
address [Halley-2008]. Cache poisoning occurs after the requested
site's name servers resolve the request and attempt to forward the
true IP back to the requesting device; on the return route the
resolved IP is recursively cached by each DNS server that initially
forwarded the request. During this caching process if an undesirable
keyword is recognized, the resolved IP is "poisoned" and an
alternative IP (or NXDOMAIN error) is returned more quickly than the
upstream resolver can respond, causing a forged IP address to be
cached (and potentially recursively so). The alternative IPs usually
direct to a nonsense domain or a warning page. Alternatively,
Iranian censorship appears to prevent the communication en-route,
preventing a response from ever being sent [Aryan-2012].
There are also cases of what is colloquially called "DNS lying",
where a censor mandates that the DNS responses provided -- by an
operator of a recursive resolver such as an Internet access provider
-- be different than what 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. It can be circumvented by using alternative DNS resolvers
(such as any of the public DNS resolvers) that may fall outside of
the jurisdictional control of the censor, or Virtual Private Network
(VPN) technology. DNS mangling and cache poisoning also imply
returning an incorrect IP to those attempting to resolve a domain
name, but in some cases the destination may be technically
accessible; over HTTP, for example, the user may have another method
of obtaining the IP address of the desired site and may be able to
access it if the site is configured to be the default server
listening at this IP address. Target blocking has also been a
problem, as occasionally users outside of the 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 are hard to imagine given limited
deployment of DNSSEC and limited client support for DNSSEC
validation). Note that an adversary seeking to merely block
resolution can serve a DNSSEC record that doesn't validate correctly,
assuming of course that the client/recursive resolver validates.
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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 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, Iran, Turkey, and the United States have discussed blocking
entire TLDs as well, but only Iran has acted by blocking all Israeli
(.il) domains [Albert-2011]. DNS-blocking is commonly deployed in
European countries to deal with undesirable content, such as child
abuse content (Norway, United Kingdom, Belgium, Denmark, Finland,
France, Germany, Ireland, Italy, Malta, the Netherlands, Poland,
Spain and Sweden [Wright-2013] [Eneman-2010]), online gambling
(Belgium, Bulgaria, Czech Republic, Cyprus, Denmark, Estonia, France,
Greece, Hungary, Italy, Latvia, Lithuania, Poland, Portugal, Romania,
Slovakia, Slovenia, Spain (see Section 6.3.2 of: [EC-gambling-2012],
[EC-gambling-2019])), copyright infringement (all European Economic
Area countries), hate-speech and extremism (France [Hertel-2015]) and
terrorism content (France [Hertel-2015]).
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
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no alternatives. Traffic shaping techniques that rate-limit the
bandwidth available to certain types of traffic is one example of a
performance degradation.
Trade offs: While implementing a performance degradation will not
always eliminate the ability of people to access a desire resource,
it may force them to use other means of communication where
censorship (or surveillance) is more easily accomplished.
Empirical Examples: Iran has been known to shape the bandwidth
available to HTTPS traffic to encourage unencrypted HTTP traffic
[Aryan-2012].
5.2.2. Packet Dropping
Packet dropping is a simple mechanism to prevent undesirable traffic.
The censor identifies undesirable traffic and chooses to not properly
forward any packets it sees associated with the traversing
undesirable traffic instead of following a normal routing protocol.
This can be paired with any of the previously described mechanisms so
long as the censor knows the user must route traffic through a
controlled router.
Trade offs: Packet Dropping is most successful when every traversing
packet has transparent information linked to undesirable content,
such as a Destination IP. One downside Packet Dropping suffers from
is the necessity of blocking all content from otherwise allowable IPs
based on a single subversive sub-domain; blogging services and github
repositories are good examples. China famously dropped all github
packets for three days based on a single repository hosting
undesirable content [Anonymous-2013]. The need to inspect every
traversing packet in close to real time also makes Packet Dropping
somewhat challenging from a QoS perspective.
Empirical Examples: Packet Dropping is a very common form of
technical interference and lends itself to accurate detection given
the unique nature of the time-out requests it leaves in its wake.
The Great Firewall of China has been observed using packet dropping
as one of its primary technical censorship mechanisms [Ensafi-2013].
Iran has also used Packet Dropping as the mechanism for throttling
SSH [Aryan-2012]. These are but two examples of a ubiquitous
censorship practice. Notably, packet dropping during the handshake
or working connection is the only interference technique observed for
QUIC traffic to date (e.g., in India, Iran, Russia and Uganda
[Elmenhorst-2021][Elmenhorst-2022]).
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5.2.3. RST Packet Injection
Packet injection, generally, refers to a man-in-the-middle (MITM)
network interference technique that spoofs packets in an established
traffic stream. RST packets are normally used to let one side of 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 setup. While QUIC implements a stateless reset
mechanism, such a reset is only accepted by a peer if the packet ends
in a previously issued (stateless reset) token which is 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
[I-D.ietf-quic-transport] for more details.)
Trade offs: Although ineffective against non-TCP protocols (QUIC,
IPSec), RST Packet Injection has a few advantages that make it
extremely popular as a technique employed for censorship. RST Packet
Injection is an out-of-band interference mechanism, allowing the
avoidance of the QoS bottleneck one can encounter with inline
techniques such as Packet Dropping. This out-of-band property allows
a censor to inspect a copy of the information, usually mirrored by an
optical splitter, making it an ideal pairing for DPI and protocol
identification [Weaver-2009] (this asynchronous version of a MITM is
often called a Man-on-the-Side (MOTS)). RST Packet Injection also
has the advantage of only requiring one of the two endpoints to
accept the spoofed packet for the connection to be interrupted.
The difficult part of RST Packet Injection is spoofing "enough"
correct information to ensure one end-point accepts an RST packet as
legitimate; this generally implies a correct IP, port, and TCP
sequence number. Sequence number is the hardest to get correct, as
[RFC0793] specifies an RST Packet should be in-sequence to be
accepted, although the RFC also recommends allowing in-window packets
as "good enough". This in-window recommendation is important; 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
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[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
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Network Disconnection to help Junta forces quash a rebellion in 2007
[Dobie-2007]. China disconnected the network in the Xinjiang region
during unrest in 2009 in an effort to prevent the protests from
spreading to other regions [Heacock-2009]. The Arab Spring saw the
the most frequent usage of Network Disconnection, with events in
Egypt and Libya in 2011 [Cowie-2011], and Syria in 2012
[Thomson-2012]. Russia indicated that it would attempt to disconnect
all Russian networks from the global Internet in April 2019 as part
of a test of the nation's network independence. Reports also
indicate that, as part of the test disconnect, Russian
telecommunications firms must now route all traffic to state-operated
monitoring points [Cimpanu-2019]. India saw the largest number of
Internet shutdowns per year in 2016 and 2017 [Dada-2017].
5.3.2. Adversarial Route Announcement
More fine-grained and potentially wide-spread censorship can be
achieved with BGP hijacking, which adversarially re-routes BGP IP
prefixes incorrectly within a region and beyond. This restricts and
effectively censors the correctly known location of information that
flows into or out of a jurisdiction and will similarly prevent people
from outside your jurisdiction from viewing content generated outside
your jurisdiction as the adversarial route announcement propagates.
The first can be achieved by an adversarial BGP announcement of
incorrect routes that are not intended to leak beyond a jurisdiction,
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 it lost control
of several million of its IP addresses. Those IP prefixes were being
misdirected to China Telecom, a Chinese government-owned ISP
[Google-2018]}, in a manner similar to the BGP hijacking of US
government and military websites by China Telecom in 2010. ISPs in
both Russia (2022) and Myanmar (2021) have tried to hijack the same
Twitter prefix more than once [MANRS].
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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], but 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,
a crash attack aims to crash the service so resources can be
reallocated elsewhere without "releasing" the service.
Trade offs: DDoS is an appealing mechanism when a censor would like
to prevent all access to undesirable content, instead of only
preventing access in their region for a limited period of time. The
latter is really the only uniquely beneficial feature for DDoS as a
technique employed for censorship. The resources required to carry
out a successful DDoS against major targets are computationally
expensive, usually requiring 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 [Schone-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 collocated with the
Great Firewall, dubbed "Great Cannon", that was able to inject
JavaScript code into web visits to a Chinese search engine that
commandeered those user agents to send DDoS traffic to various sites
[Marczak-2015].
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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/ISP level --
China's army of monitors is a good example [BBC-2013b] -- but more
commonly manual filtering occurs on an institutional level. Internet
Content Providers such as Google or Weibo, require a business license
to operate in China. One of the prerequisites for a business license
is an agreement to sign a "voluntary pledge" known as the "Public
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Pledge on Self-discipline for the Chinese Internet Industry". The
failure to "energetically uphold" the pledged values can lead to the
ICPs being held liable for the offending content by the Chinese
government [BBC-2013b].
6.2. Self-Censorship
Self-censorship is difficult to document, as it manifests primarily
through a lack of undesirable content. Tools which encourage self-
censorship are those which may lead a prospective speaker to believe
that speaking increases the risk of unfavourable outcomes for the
speaker (technical monitoring, identification requirements, etc.).
Reporters Without Borders exemplify methods of imposing self-
censorship in their annual World Press Freedom Index reports
[RWB2020].
6.3. Server Takedown
As mentioned in passing by [Murdoch-2011], servers must have a
physical location somewhere in the world. If undesirable content is
hosted in the censoring country, the servers can be physically seized
or -- in cases where a server is virtualized in a cloud
infrastructure where it may not necessarily have a fixed physical
location -- the hosting provider can be required to prevent access.
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 which
registered the domain name through a legal procedure grounded in
either private contracts or public law. Domain name seizures is
increasingly used by both public authorities and private entities to
deal with undesired content dissemination [ICANN2012] [EFF2017].
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7. Future work
In addition to establishing a thorough resource for describing
censorship techniques, this document implicates critical areas for
future work.
Taken as a whole the apparent costs of implementation of censorship
techniques indicate a need for better classification of censorship
regimes as they evolve and mature, and specifying censorship
circumvention techniques themselves. Censors maturity refers to the
technical maturity required of the censor to perform the specific
censorship technique. Future work might classify techniques by
essentially how hard a censor must work, including what
infrastructure is required, in order to successfully censor content,
users or services.
On circumvention, the increase in protocols leveraging encryption is
an effective counter-measure against some forms of censorship
described in this document, but that thorough research on
circumvention and encryption be left for another document. Moreover
the censorship circumvention community has developed an area of
research on "pluggable transports," which collects, documents and
makes agile methods for obfuscating the on-path traffic of censorship
circumvention tools such that it appears indistinguishable from other
kinds of traffic [Tor-2020]. Those methods would benefit from future
work in the internet standards community, too.
Lastly the empirical examples demonstrate that censorship techniques
can evolve quickly, and experience shows that this document can only
be a point-in-time statement. Future work might extend this document
with updates and new techniques described using a comparable
methodology.
8. Contributors
This document benefited from discussions with and input from David
Belson, Stephane Bortzmeyer, Vinicius Fortuna, Gurshabad Grover,
Andrew McConachie, Martin Nilsson, Michael Richardson, Patrick Vacek
and Chris Wood.
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a takedown order from Spain", 2019,
<https://techcrunch.com/2019/10/30/github-removes-tsunami-
democratics-apk-after-a-takedown-order-from-spain/>.
[MANRS] Siddiqui, A., "Lesson Learned: Twitter Shored Up Its
Routing Security", 2022, <https://www.manrs.org/2022/03/
lesson-learned-twitter-shored-up-its-routing-security/>.
[Marczak-2015]
Marczak, B., Weaver, N., Dalek, J., Ensafi, R., Fifield,
D., McKune, S., Rey, A., Scott-Railton, J., Deibert, R.,
and V. Paxson, "An Analysis of China’s “Great Cannon”",
2015,
<https://www.usenix.org/system/files/conference/foci15/
foci15-paper-marczak.pdf>.
[Muncaster-2013]
Muncaster, P., "Malaysian election sparks web blocking/
DDoS claims", 2013,
<http://www.theregister.co.uk/2013/05/09/
malaysia_fraud_elections_ddos_web_blocking/>.
[Murdoch-2011]
Murdoch, S. J. and R. Anderson, "Access Denied: Tools and
Technology of Internet Filtering", 2011,
<http://access.opennet.net/wp-content/uploads/2011/12/
accessdenied-chapter-3.pdf>.
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[NA-SK-2019]
Morgus, R., Sherman, J., and S. Nam, "Analysis: South
Korea's New Tool for Filtering Illegal Internet Content",
2019, <https://www.newamerica.org/cybersecurity-
initiative/c2b/c2b-log/analysis-south-koreas-sni-
monitoring/>.
[Nabi-2013]
Nabi, Z., "The Anatomy of Web Censorship in Pakistan",
2013, <http://0b4af6cdc2f0c5998459-c0245c5c937c5dedcca3f17
64ecc9b2f.r43.cf2.rackcdn.com/12387-foci13-nabi.pdf>.
[Netsec-2011]
n3t2.3c, "TCP-RST Injection", 2011,
<https://nets.ec/TCP-RST_Injection>.
[OONI-2018]
Evdokimov, L., "Iran Protests: DPI blocking of Instagram
(Part 2)", 2018,
<https://ooni.org/post/2018-iran-protests-pt2/>.
[OONI-2019]
Singh, S., Filastò, A., and M. Xynou, "China is now
blocking all language editions of Wikipedia", 2019,
<https://ooni.org/post/2019-china-wikipedia-blocking/>.
[Orion-2013]
Orion, E., "Zimbabwe election hit by hacking and DDoS
attacks", 2013,
<http://www.theinquirer.net/inquirer/news/2287433/
zimbabwe-election-hit-by-hacking-and-ddos-attacks>.
[Patil-2019]
Patil, S. and N. Borisov, "What Can You Learn from an
IP?", 2019, <https://irtf.org/anrw/2019/
anrw2019-final44-acmpaginated.pdf>.
[Porter-2010]
Porter, T., "The Perils of Deep Packet Inspection", 2010,
<http://www.symantec.com/connect/articles/perils-deep-
packet-inspection>.
[Rambert-2021]
Rampert, R., Weinberg, Z., Barradas, D., and N. Christin,
"Chinese Wall or Swiss Cheese? Keyword filtering in the
Great Firewall of China", 2021,
<https://www.andrew.cmu.edu/user/nicolasc/publications/
Rambert-WWW21.pdf>.
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[Reda-2017]
Reda, J., "New EU law prescribes website blocking in the
name of 'consumer protection'", 2017,
<https://juliareda.eu/2017/11/eu-website-blocking/>.
[RFC0793] Postel, J., "Transmission Control Protocol", RFC 793,
DOI 10.17487/RFC0793, September 1981,
<https://www.rfc-editor.org/rfc/rfc793>.
[RFC6066] Eastlake 3rd, D., "Transport Layer Security (TLS)
Extensions: Extension Definitions", RFC 6066,
DOI 10.17487/RFC6066, January 2011,
<https://www.rfc-editor.org/rfc/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/rfc/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/rfc/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/rfc/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/rfc/rfc8484>.
[RSF-2005] Reporters Sans Frontieres, "Technical ways to get around
censorship", 2005, <http://archives.rsf.org/print-
blogs.php3?id_article=15013>.
[Rushe-2015]
Rushe, D., "Bing censoring Chinese language search results
for users in the US", 2013,
<http://www.theguardian.com/technology/2014/feb/11/bing-
censors-chinese-language-search-results>.
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[RWB2020] Reporters Without Borders, "2020 World Press Freedom
Index: Entering a decisive decade for journalism,
exacerbated by coronavirus", 2020, <https://rsf.org/
en/2020-world-press-freedom-index-entering-decisive-
decade-journalism-exacerbated-coronavirus>.
[Sandvine-2014]
Sandvine, "Technology Showcase on Traffic Classification:
Why Measurements and Freeform Policy Matter", 2014,
<https://www.sandvine.com/downloads/general/technology/
sandvine-technology-showcases/sandvine-technology-
showcase-traffic-classification.pdf>.
[Satija-2021]
Satija, S. and R. Chatterjee, "BlindTLS: Circumventing
TLS-based HTTPS censorship", 2021,
<https://sambhav.info/files/blindtls-foci21.pdf>.
[Schoen-2007]
Schoen, S., "EFF tests agree with AP: Comcast is forging
packets to interfere with user traffic", 2007,
<https://www.eff.org/deeplinks/2007/10/eff-tests-agree-ap-
comcast-forging-packets-to-interfere>.
[Schone-2014]
Schone, M., Esposito, R., Cole, M., and G. Greenwald,
"Snowden Docs Show UK Spies Attacked Anonymous, Hackers",
2014, <http://www.nbcnews.com/feature/edward-snowden-
interview/exclusive-snowden-docs-show-uk-spies-attacked-
anonymous-hackers-n21361>.
[Senft-2013]
Senft, A., "Asia Chats: Analyzing Information Controls and
Privacy in Asian Messaging Applications", 2013,
<https://citizenlab.org/2013/11/asia-chats-analyzing-
information-controls-privacy-asian-messaging-
applications/>.
[Shbair-2015]
Shbair, W. M., Cholez, T., Goichot, A., and I. Chrisment,
"Efficiently Bypassing SNI-based HTTPS Filtering", 2015,
<https://hal.inria.fr/hal-01202712/document>.
[SIDN2020] Moura, G., "Detecting and Taking Down Fraudulent Webshops
at the .nl ccTLD", 2020,
<https://labs.ripe.net/Members/giovane_moura/detecting-
and-taking-down-fraudulent-webshops-at-a-cctld>.
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[Singh-2019]
Singh, K., Grover, G., and V. Bansal, "How India Censors
the Web", 2019, <https://arxiv.org/abs/1912.08590>.
[Sophos-2015]
Sophos, "Understanding Sophos Web Filtering", 2015,
<https://www.sophos.com/en-us/support/
knowledgebase/115865.aspx>.
[SSAC-109-2020]
ICANN Security and Stability Advisory Committee, "SAC109:
The Implications of DNS over HTTPS and DNS over TLS",
2020, <https://www.icann.org/en/system/files/files/sac-
109-en.pdf>.
[Tang-2016]
Tang, C., "In-depth analysis of the Great Firewall of
China", 2016,
<https://www.cs.tufts.edu/comp/116/archive/fall2016/
ctang.pdf>.
[Thomson-2012]
Thomson, I., "Syria Cuts off Internet and Mobile
Communication", 2012,
<http://www.theregister.co.uk/2012/11/29/
syria_internet_blackout/>.
[Tor-2020] The Tor Project, "Tor: Pluggable Transports", 2020,
<https://2019.www.torproject.org/docs/pluggable-
transports.html.en>.
[Trustwave-2015]
Trustwave, "Filter: SNI extension feature and HTTPS
blocking", 2015,
<https://www3.trustwave.com/software/8e6/hlp/r3000/
files/1system_filter.html>.
[Tschantz-2016]
Tschantz, M., Afroz, S., Anonymous, A., and V. Paxson,
"SoK: Towards Grounding Censorship Circumvention in
Empiricism", 2016,
<https://oaklandsok.github.io/papers/tschantz2016.pdf>.
[Verkamp-2012]
Verkamp, J. P. and M. Gupta, "Inferring Mechanics of Web
Censorship Around the World", 2012,
<https://www.usenix.org/system/files/conference/foci12/
foci12-final1.pdf>.
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[Victor-2019]
Victor, D., "Blizzard Sets Off Backlash for Penalizing
Hearthstone Gamer in Hong Kong", 2019,
<https://www.nytimes.com/2019/10/09/world/asia/blizzard-
hearthstone-hong-kong.html>.
[Villeneuve-2011]
Villeneuve, N., "Open Access: Chapter 8, Control and
Resistance, Attacks on Burmese Opposition Media", 2011,
<http://access.opennet.net/wp-content/uploads/2011/12/
accesscontested-chapter-08.pdf>.
[VonLohmann-2008]
VonLohmann, F., "FCC Rules Against Comcast for BitTorrent
Blocking", 2008, <https://www.eff.org/deeplinks/2008/08/
fcc-rules-against-comcast-bit-torrent-blocking>.
[Wagner-2009]
Wagner, B., "Deep Packet Inspection and Internet
Censorship: International Convergence on an ‘Integrated
Technology of Control'", 2009,
<http://advocacy.globalvoicesonline.org/wp-
content/uploads/2009/06/deeppacketinspectionandinternet-
censorship2.pdf>.
[Wagstaff-2013]
Wagstaff, J., "In Malaysia, online election battles take a
nasty turn", 2013,
<http://www.reuters.com/article/2013/05/04/uk-malaysia-
election-online-idUKBRE94309G20130504>.
[Wang-2017]
Wang, Z., Cao, Y., Qian, Z., Song, C., and S.
Krishnamurthy, "Your State is Not Mine: A Closer Look at
Evading Stateful Internet Censorship", 2017,
<https://www.cs.ucr.edu/~zhiyunq/pub/
imc17_censorship_tcp.pdf>.
[Wang-2020]
Wang, Z., Zhu, S., Cao, Y., Qian, Z., Song, C.,
Krishnamurthy, S., Chan, K., and T. Braun, "SYMTCP:
Eluding Stateful Deep Packet Inspection with Automated
Discrepancy Discovery", 2020,
<https://www.cs.ucr.edu/~zhiyunq/pub/ndss20_symtcp.pdf>.
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[Weaver-2009]
Weaver, N., Sommer, R., and V. Paxson, "Detecting Forged
TCP Packets", 2009, <http://www.icir.org/vern/papers/
reset-injection.ndss09.pdf>.
[Whittaker-2013]
Whittaker, Z., "1,168 keywords Skype uses to censor,
monitor its Chinese users", 2013,
<http://www.zdnet.com/1168-keywords-skype-uses-to-censor-
monitor-its-chinese-users-7000012328/>.
[Wikip-DoS]
Wikipedia, "Denial of Service Attacks", 2016,
<https://en.wikipedia.org/w/index.php?title=Denial-of-
service_attack&oldid=710558258>.
[Wilde-2012]
Wilde, T., "Knock Knock Knockin' on Bridges Doors", 2012,
<https://blog.torproject.org/blog/knock-knock-knockin-
bridges-doors>.
[Winter-2012]
Winter, P., "How China is Blocking Tor", 2012,
<http://arxiv.org/pdf/1204.0447v1.pdf>.
[WP-Def-2020]
Wikipedia contributors, "Censorship", 2020,
<https://en.wikipedia.org/w/
index.php?title=Censorship&oldid=943938595>.
[Wright-2013]
Wright, J. and Y. Breindl, "Internet filtering trends in
liberal democracies: French and German regulatory
debates", 2013,
<https://policyreview.info/articles/analysis/internet-
filtering-trends-liberal-democracies-french-and-german-
regulatory-debates>.
[Zhu-2011] Zhu, T., "An Analysis of Chinese Search Engine Filtering",
2011,
<http://arxiv.org/ftp/arxiv/papers/1107/1107.3794.pdf>.
[Zmijewski-2014]
Zmijewski, E., "Turkish Internet Censorship Takes a New
Turn", 2014,
<https://blogs.oracle.com/internetintelligence/turkish-
internet-censorship-takes-a-new-turn>.
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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
Hall, et al. Expires 30 September 2023 [Page 45]
