Nick Mathewson
2018-11-27 13:23:21 UTC
# Towards Side Channel Analysis of Datagram Tor vs Current Tor
Version 0.6, 27 Nov 2018
by Nick Mathewson and Mike Perry
## Disclaimers
This whitepaper assumes that you know how Tor works.
There are probably some very good references here that we didn't
remember to cite.
## Introduction
Tor's current design requires that its data cells be transmitted
from one end of a circuit to the other using a reliable, in-order
delivery mechanism. To meet this requirement, Tor relays need to
buffer cells--spending resources, hurting performance, and risking
susceptibility to out-of-memory attacks.
In order to improve Tor's performance and resilience, researchers
have made several proposals for ways to relax the requirement for
reliable in-order delivery. In general, these "datagram-based"
proposals would allow relays to drop or reorder cells as needed,
and move the responsibility for providing a reliable stream protocol
to the endpoints (the client and the exit relays).
But by increasing flexibility for the relays, and by increasing the
complexity of the endpoints, these datagram proposals also create
some new attack vectors. Before we can deploy any of these designs,
we need to consider whether these attacks weaken Tor's security, or
whether they are irrelevant given other, stronger attacks against
Onion Routing.
This whitepaper tries to list these attacks, and to provide a
framework for thinking about them as we move forward with our design
analysis.
We hope that this whitepaper will help researchers and others in the Tor
community to understand these issues, so that we can work together to
find new ideas to analyze and mitigate the attacks described here, and
to help deploy a faster and more reliable network while still
maintaining our current (or better) security guarantees. We hope that
our description of the problem space will inspire, not discourage,
future experiments in this area, and help with a holistic understanding
of the risks, rewards, and future areas of work.
### A toy system
We will be analyzing a system that differs from Tor in the following
ways.
* The link between a client and its guard, and between each pair
of relays uses DTLS over UDP: packets can be dropped or
re-ordered by an attacker on the link, but not modified, read,
or forged. Each DTLS packet contains an integer number of cells.
* Each circuit between a client and an exit traverse several
relays, as before. The cells on a circuit are no longer
guaranteed to arrive reliably, but can be dropped or re-ordered
on the wire, or by a relay.
* To provide reliable service end-to-end, the client and the
exit each use a TCP-like protocol to track which application
bytes have been sent and received. Received data is
acknowledged; dropped data is retransmitted.
* The cryptography to be used for circuit encryption is not
specified here.
* A reliable signaling mechanism between relays (to create,
destroy, and maintain circuits) is not specified here.
(It is likely that many readers will be able to design a system that
resists the attacks below better than the design above. But please
remember as you do, that a design which improves a system in one way
may constrain it in others, or may offer insufficient benefits to be
clearly superior to Tor as it is today. Before we can deploy, we
will need not just defenses, but also a systemic way to compare the
effect of these defenses, used together, to the Tor status quo.)
## Some preexisting attacks to consider
To put the datagram-based attacks into context, we'll start out by
listing some attacks against the current non-datagram Tor design
(and proposed defenses for those, where they exist).
We assume, as usual, an adversary who controls some but not all
relays, and some but not all ISPs.
A note on attack power: the accuracy of many of these attacks,
particularly the passive ones, depends on the type of traffic being
sent, the quantity of similar traffic elsewhere on the Tor network,
the quantity of concurrent activity by the same client, the
adversary's observation position and data retention resolution, the
quantity of padding, and the tendency of the network to preserve or
alter packet timing information in transit.
In many cases, we don't have good metrics or evaluation methodology
to determine how much harder or easier one attack is than another.
### End-to-end passive traffic correlation attacks.
Here's the gold-standard base-line attack: an attacker who can watch
any two points on the same circuit is assumed to be able to realize,
without having observed very much traffic at all, that the two
points are indeed on the same circuit by correlating the timing and
volume of data sent at those two points.
When one of these points is also linked to the client, and one is
linked to the client's activity, this attack deanonymizes the
client.
Tor's current design focuses on minimizing this probability, and
also shifting its characteristics, through things like network
diversity and long-term entry points. The attack may also become
harder (and/or slower) when there is a lot of similar concurrent
traffic on the Tor
network, which means that adding users who use Tor for many things
is in itself a form of mitigation.
Proposed defenses in this area include deliberate obfuscation of
message volume through padding, and of message timing through random
delays, as well as things like traffic splitting and more complex
traffic scheduling for loud flows. While we have completed some work on
link padding, and are progressing on a deployment for circuit
padding, it is not yet clear if we can use these defenses in an
affordable way against a correlation attack, and it is hard to
measure their effectiveness on a realistic Tor-sized network.
### Data tagging side-channels by relays
If two relays are on the same circuit, they can surreptitiously
communicate with one another transforming the data in the RELAY
cells, and un-transforming the data before passing it on. Since
Tor's current encryption protocol is malleable, this allows them to
send a large number of bits per cell.
This attack can also be used when two relays do not know if they are
on the same circuit. One relay modifies a cell, and the other one
looks for such modifications. If the data is processed by an honest
relay, it will destroy the circuit, but the client may or may not
notice that the circuit has destroyed. (And the dishonest relay may
delay informing the client!)
To defend against this, we plan to replace our encryption with a
non-malleable algorithm. See for example proposals 202, 261, and
295.
### Destructive side-channels (internal)
Even if we remove the malleability in Tor's encryption, a smaller
side-channel remains: A dishonest relay can destroy a circuit at any
time, either by corrupting the circuit or simply sending a DESTROY
cell along it. A third party can destroy a large number of circuits
at once by remotely attacking a client or relay -- either disabling
that relay, or making it close circuits because of the OOM
handler. (See the Sniper Attack paper.)
If a circuit is corrupted (as would happen if a relay attempted data
tagging against one of the non-malleable cryptographic algorithms
mentioned above), other points on the circuit can tell which cell is
the first corrupted cell. If a circuit is destroyed at one point,
other points on the circuit can tell how many cells were sent before
the destruction.
It is likely that based on data or traffic patterns, most parties on
a circuit will be able to distinguish a prematurely destroyed
circuit from one that was shut down normally.
In each case, this attack can be used to send (log n) bits of
information per circuit, at the cost of destroying the circuit,
where n is the number of cells that might be sent over the circuit in
total. Some noise will exist, since we expect some circuits to be
prematurely closed on their own. We don't know how much noise.
We also have various heuristics that can attempt to detect if this
happens too often; however at best they likely reduce the rate that
information that can be sent in this way rather than eliminate it.
We also lack methodology to measure the rate of information in this
case, to help determine if we can successfully reduce it further.
### Destructive network probes (external)
Though TLS is resilient against many forms of active attacks, it
can't resist an attacker who focuses against the underlying TCP
layer. Such an attacker can, by forging TCP resets, cause all the
entire TLS connection to be dropped, thereby closing all the circuits
on it. This kind of attack can be observed at other points on the
network in a way similar to the destructive side-channels noted above.
This class of attack seems to be easier against Tor's current design
than it would be against (some) datagram-based designs, since
datagram-based designs are resilient to more kinds of traffic
interference.
### Timing-based watermarking attacks
Hostile relays can also introduce a side channels to a circuit by
introducing patterned delays into the cells. For example, a relay
could buffer a large number of cells, then transmit a "1" bit by
sending a cell in a given time period, or a "0" by not sending cells
in that time period.
An attacker can also mount this attack without controlling relays:
if the attacker performs a DoS attack against a relay or its
traffic, it can observe changes in the traffic volume elsewhere on
the network.
[See https://www.freehaven.net/anonbib/cache/ccs07-latency-leak.pdf and
http://cybercentre.cs.ttu.ee/wp/wp-content/uploads/2017/01/crw2017_final.pdf ]
The bandwidth of this side-channel will be limited, since other
relays on the network will naturally buffer and delay traffic,
obscuring the pattern some. There are also limits to how long
packets can be delayed before the relay is no longer usable.
[See:
- Rainbow: https://www.freehaven.net/anonbib/cache/ndss09-rainbow.pdf
- Swirl: https://www.freehaven.net/anonbib/cache/ndss11-swirl.pdf
- Backlit (detection):
https://www.freehaven.net/anonbib/cache/acsac11-backlit.pdf ]
Proposals for resisting this type of watermarking attack are mostly
of the same type that would be needed for resisting end-to-end
correlation. An adversary that can perform active attacks to
introduce their own unique traffic patterns intuitively seems much
stronger than one that must passively use potentially common
patterns. We lack a unified framework to tell us how much stronger
this adversary is than the passive one, especially against various
defenses.
### Traffic injection attacks
Related to the active timing attack, in some positions (like exit
and RP) relays can inject cells that are ignored by the other
endpoint. These injected patterns will not impact the user's
experience, but will allow unique traffic patterns to be sent and
detected by the adversary at crucial times.
[See
https://petsymposium.org/2018/files/papers/issue2/popets-2018-0011.pdf]
These injection attacks arise from former adherence to Postel's
Maxim. Tor has since departed from this maxim, and instead opted for
stricter forward compatibility through feature versioning, but
removing instances in the codebase where injected cells can be
permitted has proven challenging.
## Attacks unique to datagram designs
Here are some attacks that are enabled by (or at any rate behave
differently under) datagram-based designs.
### Traffic-stream tagging (by relays and internet links)
Because the new system permits a number of transformations on
traffic that were not previously allowed, we need to look at how
those transformations can be used to attack users.
As a trivial example, any router can relay an arbitrary subset of
the cells that it receives on a circuit, in an arbitrary order, due
to the exact properties the reliable transport aims to provide. The
pattern induced in this way will be detectable by the exit relay
when it attempts to reconstruct the stream. Because we explicitly
allow this kind of transformation, the circuit will not be killed
after a single dropped cell, but rather will continue working
silently.
Moreover, any ISP can mount the same attack by dropping and/or
re-ordering DTLS calls.
A remote attacker may also be able to mount this attack by flooding
any router between a client and its guard, thereby causing some of
the DTLS messages to get dropped.
If we are using TCP between client and exit, the acknowledgments
sent by each endpoint will provide confirmation about which data it
received and which it did not. If instead of TCP, we use some other
protocol where the end-points communicate even more information
about which packets they did and did not receive, this can provide
an even higher-bandwidth side-channel.
The bandwidth of this side-channel is fairly high, since it allows
the attacker to send over a bit per cell. But it will be somewhat
noisy, since some cells will dropped and reordered naturally.
Padding, traffic splitting, and concurrent activity will increase
the noise of this attack; we lack metrics to tell us how much, and
we have no framework as of yet to measure the throughput of the
resulting side channel in these conditions.
### Traffic Fingerprinting of TCP-like systems
Today, because Tor terminates TCP at the guard node, there is
limited ability for the exit node to fingerprint client TCP
behavior (aside from perhaps measuring some effects on traffic
volume, but those are not likely preserved across the Tor network).
However, when using a TCP-like system for end-to-end congestion
control, flow control, and reliability, the exit relay will be able
to make inferences about client implementation and conditions based
on its behavior.
Different implementations of TCP-like systems behave differently.
Either party on a stream can observe the packets as they arrive to
notice cells from an unusual implementation. They can probe the
other side of the stream, nmap-style, to see how it responds to
various inputs.
If two TCP-like implementations differ in their retransmit or timeout
behavior, an attacker can use this to distinguish them by carefully
chosen patterns of dropped traffic. Such an attacker does not even
need to be a relay, if it can cause DTLS packets between relays to
be dropped or reordered.
This class of attacks is solvable, especially if the exact same
TCP-like implementation is used by all clients, but it also requires
careful consideration and additional constraints to be placed on the
TCP stack(s) in use that are not usually considered by TCP
implementations -- particularly to ensure that they do not depend on
OS-specific features or try to learn things about their environment
over time, across different connections.
### Retransmit-based watermarking
Even if all TCP-like implementations are identical, they will
retransmit with different timing and volume based on which cells
have been acked or not acked. These differences may be observable
from many points on the circuit, or from outside the network. Such
retransmissions can be induced from outside the network, by hostile
relays, or even by a hostile endpoint that pretends not to have
received some of the packets.
We again lack metrics to indicate that it is substantially worse
(or not worse) than other similar attacks. Intuitively, the key
difference in degree would come from how much easier it is to
perform this attack than the delay based watermarking attacks on
traditional Tor above.
### Congestion and flow control interference
To the extent that the TCP-like stack uses information learned from
one stream to alter its behavior on another stream, an attacker can
exploit this interference between streams make all of the streams
from a given party more linkable.
All implementations will have some amount of interference, to the
extent that their bandwidth is limited. But some may have more than
necessary.
### Non-malleable encryption designs only currently exist for in-order
transports (or the return of data tagging attacks)
Our proposed defenses against data tagging require us to move to
non-malleable encryption, with each cell's encryption tweaked by a
function of all previous cells, so that if even a single cell is
modified, not only is that cell corrupted, but no subsequent cell
can be decrypted.
It seems nontrivial to achieve this property with datagram based
designs, since we require that cells on a circuit can be decrypted
even when previous cells have not arrived. We can achieve
data-based non-malleability by using a per-hop MAC for each cell --
but we would no longer be able to get the property that a since
altered cell would make the whole circuit unrecoverable. This would
enable a one-bit-per-cell side-channel, similar but possibly more
powerful than the packet dropping side-channel above. (Because the
congestion window is essentially a bit vector of received cells,
the adversary in this scenario gets to corrupt cells in carefully
chosen ways instead of merely dropping them.)
Perhaps other cryptographic schemes could be found to resist
data-tagging in a datagram-based environment or limit its impact,
but we'll need to figure out what the requirements and models are.
As a proof-by-example of a mitigating system: Proposal 253 describes
a way to send a rolling MAC out of band, to ensure integrity of
packets between those cells. But can we do better? Can middle nodes
enforce integrity in some other way?
### The risks of success: lower latency strengthens timing attacks?
There are two factors that make timing-correlation and
timing-watermark attacks more difficult in practice: similarity
between different users' traffic, and distortion in timing patterns
caused by variance in cell latency on the network. To whatever
extent we successfully reduce this distortion by lowering latency,
it seems that we'll make these attacks more powerful.
In particular, geolocation attacks based on observed circuit setup
times may get worse [See again
https://www.freehaven.net/anonbib/cache/ccs07-latency-leak.pdf].
We're already making improvements to Tor that may make these attacks
worse -- Tor latency has dropped and will continue to drop due to
improvements like KIST, more relays, and better load balancing.
Further incremental improvements like explicit congestion control on
the existing Tor network will reduce latency even further.
It may be that a more performant Tor becomes less safe than a
slower, less usable Tor. On the other hand, a more usable Tor will
likely be used by more people, which we know makes many forms of
traffic analysis harder (slower?) in general. However, we have no way to
measure this tradeoff on many different attack types.
Delay and latency can also be added back in, and this has been a common
defense against both active adversaries and timing attacks in the
anonymity literature, but such delays have user-facing consequences,
unless they are carefully restricted to the cases where the
adversary can directly measure RTT and can be amortized away by
things like pre-emptive circuit building. In this and other cases,
it is also not clear to what degree adding delay is more useful than
adding more padding.
## Towards comparing attacks
A high-bandwidth attack is worse than a low-bandwidth attack. One
bit is enough to send "is this the targeted user?", but 32 bits is
enough to send a whole IP address.
The impact of these attacks become worse if they can be repeated
over time.
An attack that can be performed by an ISP relaying traffic is worse
than one that can be performed by a relay. An attack that can be
performed remotely against either of these is worse still.
We need some kind of methodology to help us compare the new side
channels that datagram transports may enable to the existing side
channels in Tor, particularly delay-based and congestion-based side
channels. Ideally, these metrics or evaluation methodology would
also allow us to compare these side channels under various forms of
defense, such as padding.
At the very least, we need some way to compare the side channels in
datagram transports to those that already exist.
We also likely need a common reference research prototype and/or
platform to experiment with and study, so that attacks and defenses
are reproducibly comparable. Reproducibility in attack and defense
literature is often not reliable, due to differing implementations,
in addition to differing methodology and evaluation frameworks.
## Open Questions
Why permit reordering? There are schemes (like order-preserving
encryption) that we could deploy on middle nodes to prevent
reordering, without allowing earlier nodes to differentiate
padding from non-padding. Do we derive any benefit by allowing a
relay to send cells on a single circuit in a different order than
the order in which it receives those cells on that circuit? This
may be an answered question in congestion control research, but we
lack the domain expertise to know what this tradeoff is.
Related: what cryptography to use? Our current stateful encryption
schemes benefit from having access to "all previous cells" when
encrypting or decrypting each following cell. If we allow a cell to
be {de,en}crypted before previous cells are received, we'll need a
new model for onion-routing cryptography -- possibly one with
significantly bigger headers.
## Future work
We hope to investigate these issues with researchers and others in the
Tor community as we work towards solutions to help scale and strengthen
the Tor network. Understanding the risks and rewards that datagram-based
transports introduce to Tor is important to help us select designs that
both help improve performance but also guarantee safety for Tor
users. We hope that by cataloging these risks, future conversations
about improved network designs can bring answers and broader
improvements. We look forward to working with others interested in
helping solve these problems to design a better Tor.
## Acknowledgments
Our thanks to Chelsea Komlo for many helpful suggestions and
comments on earlier drafts of this whitepaper, and for writing the
request for future work.
## Further reading
Steven Murdoch, "Comparison of Tor Datagram Designs", 2011.
https://murdoch.is/papers/tor11datagramcomparison.pdf
Mashael AlSabah and Ian Goldberg. "PCTCP: per-circuit
TCP-over-IPsec transport for anonymous communication overlay
networks", 2013.
http://cacr.uwaterloo.ca/techreports/2013/cacr2013-09.pdf
Michael F. Nowlan, David Wolinsky, and Bryan Ford.
"Reducing Latency in Tor Circuits with Unordered Delivery",
2013.
https://www.usenix.org/system/files/conference/foci13/foci13-nowlan.pdf
Rob Jansen, Florian Tschorsch, Aaron Johnson, and Björn Scheuermann
The Sniper attack: Anonymously Deanonymizing and Disabling the Tor
Network", 2013
https://www.nrl.navy.mil/itd/chacs/sites/edit-www.nrl.navy.mil.itd.chacs/files/pdfs/13-1231-3743.pdf
Version 0.6, 27 Nov 2018
by Nick Mathewson and Mike Perry
## Disclaimers
This whitepaper assumes that you know how Tor works.
There are probably some very good references here that we didn't
remember to cite.
## Introduction
Tor's current design requires that its data cells be transmitted
from one end of a circuit to the other using a reliable, in-order
delivery mechanism. To meet this requirement, Tor relays need to
buffer cells--spending resources, hurting performance, and risking
susceptibility to out-of-memory attacks.
In order to improve Tor's performance and resilience, researchers
have made several proposals for ways to relax the requirement for
reliable in-order delivery. In general, these "datagram-based"
proposals would allow relays to drop or reorder cells as needed,
and move the responsibility for providing a reliable stream protocol
to the endpoints (the client and the exit relays).
But by increasing flexibility for the relays, and by increasing the
complexity of the endpoints, these datagram proposals also create
some new attack vectors. Before we can deploy any of these designs,
we need to consider whether these attacks weaken Tor's security, or
whether they are irrelevant given other, stronger attacks against
Onion Routing.
This whitepaper tries to list these attacks, and to provide a
framework for thinking about them as we move forward with our design
analysis.
We hope that this whitepaper will help researchers and others in the Tor
community to understand these issues, so that we can work together to
find new ideas to analyze and mitigate the attacks described here, and
to help deploy a faster and more reliable network while still
maintaining our current (or better) security guarantees. We hope that
our description of the problem space will inspire, not discourage,
future experiments in this area, and help with a holistic understanding
of the risks, rewards, and future areas of work.
### A toy system
We will be analyzing a system that differs from Tor in the following
ways.
* The link between a client and its guard, and between each pair
of relays uses DTLS over UDP: packets can be dropped or
re-ordered by an attacker on the link, but not modified, read,
or forged. Each DTLS packet contains an integer number of cells.
* Each circuit between a client and an exit traverse several
relays, as before. The cells on a circuit are no longer
guaranteed to arrive reliably, but can be dropped or re-ordered
on the wire, or by a relay.
* To provide reliable service end-to-end, the client and the
exit each use a TCP-like protocol to track which application
bytes have been sent and received. Received data is
acknowledged; dropped data is retransmitted.
* The cryptography to be used for circuit encryption is not
specified here.
* A reliable signaling mechanism between relays (to create,
destroy, and maintain circuits) is not specified here.
(It is likely that many readers will be able to design a system that
resists the attacks below better than the design above. But please
remember as you do, that a design which improves a system in one way
may constrain it in others, or may offer insufficient benefits to be
clearly superior to Tor as it is today. Before we can deploy, we
will need not just defenses, but also a systemic way to compare the
effect of these defenses, used together, to the Tor status quo.)
## Some preexisting attacks to consider
To put the datagram-based attacks into context, we'll start out by
listing some attacks against the current non-datagram Tor design
(and proposed defenses for those, where they exist).
We assume, as usual, an adversary who controls some but not all
relays, and some but not all ISPs.
A note on attack power: the accuracy of many of these attacks,
particularly the passive ones, depends on the type of traffic being
sent, the quantity of similar traffic elsewhere on the Tor network,
the quantity of concurrent activity by the same client, the
adversary's observation position and data retention resolution, the
quantity of padding, and the tendency of the network to preserve or
alter packet timing information in transit.
In many cases, we don't have good metrics or evaluation methodology
to determine how much harder or easier one attack is than another.
### End-to-end passive traffic correlation attacks.
Here's the gold-standard base-line attack: an attacker who can watch
any two points on the same circuit is assumed to be able to realize,
without having observed very much traffic at all, that the two
points are indeed on the same circuit by correlating the timing and
volume of data sent at those two points.
When one of these points is also linked to the client, and one is
linked to the client's activity, this attack deanonymizes the
client.
Tor's current design focuses on minimizing this probability, and
also shifting its characteristics, through things like network
diversity and long-term entry points. The attack may also become
harder (and/or slower) when there is a lot of similar concurrent
traffic on the Tor
network, which means that adding users who use Tor for many things
is in itself a form of mitigation.
Proposed defenses in this area include deliberate obfuscation of
message volume through padding, and of message timing through random
delays, as well as things like traffic splitting and more complex
traffic scheduling for loud flows. While we have completed some work on
link padding, and are progressing on a deployment for circuit
padding, it is not yet clear if we can use these defenses in an
affordable way against a correlation attack, and it is hard to
measure their effectiveness on a realistic Tor-sized network.
### Data tagging side-channels by relays
If two relays are on the same circuit, they can surreptitiously
communicate with one another transforming the data in the RELAY
cells, and un-transforming the data before passing it on. Since
Tor's current encryption protocol is malleable, this allows them to
send a large number of bits per cell.
This attack can also be used when two relays do not know if they are
on the same circuit. One relay modifies a cell, and the other one
looks for such modifications. If the data is processed by an honest
relay, it will destroy the circuit, but the client may or may not
notice that the circuit has destroyed. (And the dishonest relay may
delay informing the client!)
To defend against this, we plan to replace our encryption with a
non-malleable algorithm. See for example proposals 202, 261, and
295.
### Destructive side-channels (internal)
Even if we remove the malleability in Tor's encryption, a smaller
side-channel remains: A dishonest relay can destroy a circuit at any
time, either by corrupting the circuit or simply sending a DESTROY
cell along it. A third party can destroy a large number of circuits
at once by remotely attacking a client or relay -- either disabling
that relay, or making it close circuits because of the OOM
handler. (See the Sniper Attack paper.)
If a circuit is corrupted (as would happen if a relay attempted data
tagging against one of the non-malleable cryptographic algorithms
mentioned above), other points on the circuit can tell which cell is
the first corrupted cell. If a circuit is destroyed at one point,
other points on the circuit can tell how many cells were sent before
the destruction.
It is likely that based on data or traffic patterns, most parties on
a circuit will be able to distinguish a prematurely destroyed
circuit from one that was shut down normally.
In each case, this attack can be used to send (log n) bits of
information per circuit, at the cost of destroying the circuit,
where n is the number of cells that might be sent over the circuit in
total. Some noise will exist, since we expect some circuits to be
prematurely closed on their own. We don't know how much noise.
We also have various heuristics that can attempt to detect if this
happens too often; however at best they likely reduce the rate that
information that can be sent in this way rather than eliminate it.
We also lack methodology to measure the rate of information in this
case, to help determine if we can successfully reduce it further.
### Destructive network probes (external)
Though TLS is resilient against many forms of active attacks, it
can't resist an attacker who focuses against the underlying TCP
layer. Such an attacker can, by forging TCP resets, cause all the
entire TLS connection to be dropped, thereby closing all the circuits
on it. This kind of attack can be observed at other points on the
network in a way similar to the destructive side-channels noted above.
This class of attack seems to be easier against Tor's current design
than it would be against (some) datagram-based designs, since
datagram-based designs are resilient to more kinds of traffic
interference.
### Timing-based watermarking attacks
Hostile relays can also introduce a side channels to a circuit by
introducing patterned delays into the cells. For example, a relay
could buffer a large number of cells, then transmit a "1" bit by
sending a cell in a given time period, or a "0" by not sending cells
in that time period.
An attacker can also mount this attack without controlling relays:
if the attacker performs a DoS attack against a relay or its
traffic, it can observe changes in the traffic volume elsewhere on
the network.
[See https://www.freehaven.net/anonbib/cache/ccs07-latency-leak.pdf and
http://cybercentre.cs.ttu.ee/wp/wp-content/uploads/2017/01/crw2017_final.pdf ]
The bandwidth of this side-channel will be limited, since other
relays on the network will naturally buffer and delay traffic,
obscuring the pattern some. There are also limits to how long
packets can be delayed before the relay is no longer usable.
[See:
- Rainbow: https://www.freehaven.net/anonbib/cache/ndss09-rainbow.pdf
- Swirl: https://www.freehaven.net/anonbib/cache/ndss11-swirl.pdf
- Backlit (detection):
https://www.freehaven.net/anonbib/cache/acsac11-backlit.pdf ]
Proposals for resisting this type of watermarking attack are mostly
of the same type that would be needed for resisting end-to-end
correlation. An adversary that can perform active attacks to
introduce their own unique traffic patterns intuitively seems much
stronger than one that must passively use potentially common
patterns. We lack a unified framework to tell us how much stronger
this adversary is than the passive one, especially against various
defenses.
### Traffic injection attacks
Related to the active timing attack, in some positions (like exit
and RP) relays can inject cells that are ignored by the other
endpoint. These injected patterns will not impact the user's
experience, but will allow unique traffic patterns to be sent and
detected by the adversary at crucial times.
[See
https://petsymposium.org/2018/files/papers/issue2/popets-2018-0011.pdf]
These injection attacks arise from former adherence to Postel's
Maxim. Tor has since departed from this maxim, and instead opted for
stricter forward compatibility through feature versioning, but
removing instances in the codebase where injected cells can be
permitted has proven challenging.
## Attacks unique to datagram designs
Here are some attacks that are enabled by (or at any rate behave
differently under) datagram-based designs.
### Traffic-stream tagging (by relays and internet links)
Because the new system permits a number of transformations on
traffic that were not previously allowed, we need to look at how
those transformations can be used to attack users.
As a trivial example, any router can relay an arbitrary subset of
the cells that it receives on a circuit, in an arbitrary order, due
to the exact properties the reliable transport aims to provide. The
pattern induced in this way will be detectable by the exit relay
when it attempts to reconstruct the stream. Because we explicitly
allow this kind of transformation, the circuit will not be killed
after a single dropped cell, but rather will continue working
silently.
Moreover, any ISP can mount the same attack by dropping and/or
re-ordering DTLS calls.
A remote attacker may also be able to mount this attack by flooding
any router between a client and its guard, thereby causing some of
the DTLS messages to get dropped.
If we are using TCP between client and exit, the acknowledgments
sent by each endpoint will provide confirmation about which data it
received and which it did not. If instead of TCP, we use some other
protocol where the end-points communicate even more information
about which packets they did and did not receive, this can provide
an even higher-bandwidth side-channel.
The bandwidth of this side-channel is fairly high, since it allows
the attacker to send over a bit per cell. But it will be somewhat
noisy, since some cells will dropped and reordered naturally.
Padding, traffic splitting, and concurrent activity will increase
the noise of this attack; we lack metrics to tell us how much, and
we have no framework as of yet to measure the throughput of the
resulting side channel in these conditions.
### Traffic Fingerprinting of TCP-like systems
Today, because Tor terminates TCP at the guard node, there is
limited ability for the exit node to fingerprint client TCP
behavior (aside from perhaps measuring some effects on traffic
volume, but those are not likely preserved across the Tor network).
However, when using a TCP-like system for end-to-end congestion
control, flow control, and reliability, the exit relay will be able
to make inferences about client implementation and conditions based
on its behavior.
Different implementations of TCP-like systems behave differently.
Either party on a stream can observe the packets as they arrive to
notice cells from an unusual implementation. They can probe the
other side of the stream, nmap-style, to see how it responds to
various inputs.
If two TCP-like implementations differ in their retransmit or timeout
behavior, an attacker can use this to distinguish them by carefully
chosen patterns of dropped traffic. Such an attacker does not even
need to be a relay, if it can cause DTLS packets between relays to
be dropped or reordered.
This class of attacks is solvable, especially if the exact same
TCP-like implementation is used by all clients, but it also requires
careful consideration and additional constraints to be placed on the
TCP stack(s) in use that are not usually considered by TCP
implementations -- particularly to ensure that they do not depend on
OS-specific features or try to learn things about their environment
over time, across different connections.
### Retransmit-based watermarking
Even if all TCP-like implementations are identical, they will
retransmit with different timing and volume based on which cells
have been acked or not acked. These differences may be observable
from many points on the circuit, or from outside the network. Such
retransmissions can be induced from outside the network, by hostile
relays, or even by a hostile endpoint that pretends not to have
received some of the packets.
We again lack metrics to indicate that it is substantially worse
(or not worse) than other similar attacks. Intuitively, the key
difference in degree would come from how much easier it is to
perform this attack than the delay based watermarking attacks on
traditional Tor above.
### Congestion and flow control interference
To the extent that the TCP-like stack uses information learned from
one stream to alter its behavior on another stream, an attacker can
exploit this interference between streams make all of the streams
from a given party more linkable.
All implementations will have some amount of interference, to the
extent that their bandwidth is limited. But some may have more than
necessary.
### Non-malleable encryption designs only currently exist for in-order
transports (or the return of data tagging attacks)
Our proposed defenses against data tagging require us to move to
non-malleable encryption, with each cell's encryption tweaked by a
function of all previous cells, so that if even a single cell is
modified, not only is that cell corrupted, but no subsequent cell
can be decrypted.
It seems nontrivial to achieve this property with datagram based
designs, since we require that cells on a circuit can be decrypted
even when previous cells have not arrived. We can achieve
data-based non-malleability by using a per-hop MAC for each cell --
but we would no longer be able to get the property that a since
altered cell would make the whole circuit unrecoverable. This would
enable a one-bit-per-cell side-channel, similar but possibly more
powerful than the packet dropping side-channel above. (Because the
congestion window is essentially a bit vector of received cells,
the adversary in this scenario gets to corrupt cells in carefully
chosen ways instead of merely dropping them.)
Perhaps other cryptographic schemes could be found to resist
data-tagging in a datagram-based environment or limit its impact,
but we'll need to figure out what the requirements and models are.
As a proof-by-example of a mitigating system: Proposal 253 describes
a way to send a rolling MAC out of band, to ensure integrity of
packets between those cells. But can we do better? Can middle nodes
enforce integrity in some other way?
### The risks of success: lower latency strengthens timing attacks?
There are two factors that make timing-correlation and
timing-watermark attacks more difficult in practice: similarity
between different users' traffic, and distortion in timing patterns
caused by variance in cell latency on the network. To whatever
extent we successfully reduce this distortion by lowering latency,
it seems that we'll make these attacks more powerful.
In particular, geolocation attacks based on observed circuit setup
times may get worse [See again
https://www.freehaven.net/anonbib/cache/ccs07-latency-leak.pdf].
We're already making improvements to Tor that may make these attacks
worse -- Tor latency has dropped and will continue to drop due to
improvements like KIST, more relays, and better load balancing.
Further incremental improvements like explicit congestion control on
the existing Tor network will reduce latency even further.
It may be that a more performant Tor becomes less safe than a
slower, less usable Tor. On the other hand, a more usable Tor will
likely be used by more people, which we know makes many forms of
traffic analysis harder (slower?) in general. However, we have no way to
measure this tradeoff on many different attack types.
Delay and latency can also be added back in, and this has been a common
defense against both active adversaries and timing attacks in the
anonymity literature, but such delays have user-facing consequences,
unless they are carefully restricted to the cases where the
adversary can directly measure RTT and can be amortized away by
things like pre-emptive circuit building. In this and other cases,
it is also not clear to what degree adding delay is more useful than
adding more padding.
## Towards comparing attacks
A high-bandwidth attack is worse than a low-bandwidth attack. One
bit is enough to send "is this the targeted user?", but 32 bits is
enough to send a whole IP address.
The impact of these attacks become worse if they can be repeated
over time.
An attack that can be performed by an ISP relaying traffic is worse
than one that can be performed by a relay. An attack that can be
performed remotely against either of these is worse still.
We need some kind of methodology to help us compare the new side
channels that datagram transports may enable to the existing side
channels in Tor, particularly delay-based and congestion-based side
channels. Ideally, these metrics or evaluation methodology would
also allow us to compare these side channels under various forms of
defense, such as padding.
At the very least, we need some way to compare the side channels in
datagram transports to those that already exist.
We also likely need a common reference research prototype and/or
platform to experiment with and study, so that attacks and defenses
are reproducibly comparable. Reproducibility in attack and defense
literature is often not reliable, due to differing implementations,
in addition to differing methodology and evaluation frameworks.
## Open Questions
Why permit reordering? There are schemes (like order-preserving
encryption) that we could deploy on middle nodes to prevent
reordering, without allowing earlier nodes to differentiate
padding from non-padding. Do we derive any benefit by allowing a
relay to send cells on a single circuit in a different order than
the order in which it receives those cells on that circuit? This
may be an answered question in congestion control research, but we
lack the domain expertise to know what this tradeoff is.
Related: what cryptography to use? Our current stateful encryption
schemes benefit from having access to "all previous cells" when
encrypting or decrypting each following cell. If we allow a cell to
be {de,en}crypted before previous cells are received, we'll need a
new model for onion-routing cryptography -- possibly one with
significantly bigger headers.
## Future work
We hope to investigate these issues with researchers and others in the
Tor community as we work towards solutions to help scale and strengthen
the Tor network. Understanding the risks and rewards that datagram-based
transports introduce to Tor is important to help us select designs that
both help improve performance but also guarantee safety for Tor
users. We hope that by cataloging these risks, future conversations
about improved network designs can bring answers and broader
improvements. We look forward to working with others interested in
helping solve these problems to design a better Tor.
## Acknowledgments
Our thanks to Chelsea Komlo for many helpful suggestions and
comments on earlier drafts of this whitepaper, and for writing the
request for future work.
## Further reading
Steven Murdoch, "Comparison of Tor Datagram Designs", 2011.
https://murdoch.is/papers/tor11datagramcomparison.pdf
Mashael AlSabah and Ian Goldberg. "PCTCP: per-circuit
TCP-over-IPsec transport for anonymous communication overlay
networks", 2013.
http://cacr.uwaterloo.ca/techreports/2013/cacr2013-09.pdf
Michael F. Nowlan, David Wolinsky, and Bryan Ford.
"Reducing Latency in Tor Circuits with Unordered Delivery",
2013.
https://www.usenix.org/system/files/conference/foci13/foci13-nowlan.pdf
Rob Jansen, Florian Tschorsch, Aaron Johnson, and Björn Scheuermann
The Sniper attack: Anonymously Deanonymizing and Disabling the Tor
Network", 2013
https://www.nrl.navy.mil/itd/chacs/sites/edit-www.nrl.navy.mil.itd.chacs/files/pdfs/13-1231-3743.pdf