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Memory attacks on device-independent quantum cryptography.
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Physical Review Letters
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Device-independent quantum cryptographic schemes aim to guarantee security to users based only on the output statistics of any components used, and without the need to verify their internal functionality. Since this would protect users against untrustworthy or incompetent manufacturers, sabotage, or device degradation, this idea has excited much interest, and many device-independent schemes have been proposed. Here we identify a critical weakness of device-independent protocols that rely on public communication between secure laboratories. Untrusted devices may record their inputs and outputs and reveal information about them via publicly discussed outputs during later runs. Reusing devices thus compromises the security of a protocol and risks leaking secret data. Possible defenses include securely destroying or isolating used devices. However, these are costly and often impractical. We propose other more practical partial defenses as well as a new protocol structure for device-independent quantum key distribution that aims to achieve composable security in the case of two parties using a small number of devices to repeatedly share keys with each other (and no other party).
|
## Memory Attacks on Device-Independent Quantum Cryptography
Jonathan Barrett,[1, 2,][ ∗] Roger Colbeck,[3, 4,][ †] and Adrian Kent[5, 4,][ ‡]
1Department of Computer Science, University of Oxford,
Wolfson Building, Parks Road, Oxford OX1 3QD, U.K.
2Department of Mathematics, Royal Holloway, University of London, Egham Hill, Egham, TW20 0EX, U.K.
3Institute for Theoretical Physics, ETH Zurich, 8093 Zurich, Switzerland.
4Perimeter Institute for Theoretical Physics, 31 Caroline Street North, Waterloo, ON N2L 2Y5, Canada.
5Centre for Quantum Information and Foundations, DAMTP, Centre for Mathematical Sciences,
University of Cambridge, Wilberforce Road, Cambridge, CB3 0WA, U.K.
(Dated: 5[th] August 2013)
Device-independent quantum cryptographic schemes aim to guarantee security to users based
only on the output statistics of any components used, and without the need to verify their internal
functionality. Since this would protect users against untrustworthy or incompetent manufacturers,
sabotage or device degradation, this idea has excited much interest, and many device-independent
schemes have been proposed. Here we identify a critical weakness of device-independent protocols
that rely on public communication between secure laboratories. Untrusted devices may record their
inputs and outputs and reveal information about them via publicly discussed outputs during later
runs. Reusing devices thus compromises the security of a protocol and risks leaking secret data.
Possible defences include securely destroying or isolating used devices. However, these are costly
and often impractical. We propose other more practical partial defences as well as a new protocol
structure for device-independent quantum key distribution that aims to achieve composable security
in the case of two parties using a small number of devices to repeatedly share keys with each another
(and no other party).
Quantum cryptography aims to exploit the properties
of quantum systems to ensure the security of various
tasks. The best known example is quantum key distribution (QKD), which can enable two parties to share a
secret random string and thus exchange messages secure
against eavesdropping, and we mostly focus on this task
for concreteness. While all classical key distribution protocols rely for their security on assumed limitations on
an eavesdropper’s computational power, the advantage
of quantum key distribution protocols (e.g. [1, 2]) is that
they are provably secure against an arbitrarily powerful
eavesdropper, even in the presence of realistic levels of
losses and errors [3]. However, the security proofs require
that quantum devices function according to particular
specifications. Any deviation – which might arise from a
malicious or incompetent manufacturer, or through sabotage or degradation – can introduce exploitable security
flaws (see e.g. [4] for practical illustrations).
The possibility of quantum devices with deliberately
concealed flaws, introduced by an untrustworthy manufacturer or saboteur, is particularly concerning, since
(i) it is easy to design quantum devices that appear to
be following a secure protocol but are actually completely
insecure[1], and (ii) there is no general technique for identifying all possible security loopholes in standard quan
[∗Electronic address: [email protected]](mailto:[email protected])
[†Electronic address: [email protected]](mailto:[email protected])
[‡Electronic address: [email protected]](mailto:[email protected])
1 In BB84 [1], for example, a malicious state creation device could
be programmed to secretly send the basis used for the encoding
in an additional degree of freedom.
tum cryptography devices. This has led to much interest
in device-independent quantum protocols, which aim to
guarantee security on the fly by testing the device outputs [5–15]: no specification of their internal functionality is required.
Known provably secure schemes for deviceindependent quantum key distribution are inefficient,
as they require either independent isolated devices
for each entangled pair to ensure device-independent
security [6, 10–12, 16], or a large number of entangled
pairs to generate a short key [6, 16, 17]. Finding
an efficient secure device-independent quantum key
distribution scheme using two (or few) devices has
remained an open theoretical challenge. Nonetheless,
in the absence of tight theoretical bounds on the scope
for device-independent quantum cryptography, progress
to date has encouraged optimism (e.g. [18]) about the
prospects for device-independent QKD as a practical
technology, as well as for device-independent quantum
randomness expansion [13–15] and other applications of
device-independent quantum cryptography (e.g. [19]).
However, one key question has been generally neglected in work to date on device-independent quantum
cryptography, namely what happens if and when devices
are reused. Specifically, are device-reusing protocols composable – i.e. do individually secure protocols of this type
remain secure when combined? It is clear that reuse of
untrusted devices cannot be universally composable, i.e.
such devices cannot be securely reused for completely
general purposes (in particular, if they have memory,
they must be kept secure after the protocol). However,
for device-independent quantum cryptography to have
significant practical value, one would hope that devices
-----
can at least be reused for the same purpose. For example one would like to be able to implement a QKD
protocol many times, perhaps with different parties each
time, with a guarantee that all the generated keys can
be securely used in an arbitrary environment so long as
the devices are kept secure. We focus on this type of
composability here.
We describe a new type of attack that highlights pitfalls in producing protocols that are composable (in
the above sense) with device-independent security for
reusable devices, and show that for all known protocols
such composability fails in the strong sense that purportedly secret data become completely insecure. The leaks
do not exploit new side channels (which proficient users
are assumed to block), but instead occur through the
device choosing its outputs as part of a later protocol.
To illustrate this, consider a device-independent
scheme that allows two users (Alice and Bob) to generate and share a purportedly secure cryptographic key.
A malicious manufacturer (Eve) can design devices so
that they record and store all their inputs and outputs.
A well designed device-independent protocol can prevent
the devices from leaking information about the generated
key during that protocol. However, when they are reused,
the devices can make their outputs in later runs depend
on the inputs and outputs of earlier runs, and, if the protocol requires Alice and Bob to publicly exchange at least
some information about these later outputs (as all existing protocols do), this can leak information about the
original key to Eve. Moreover, in many existing protocols, such leaks can be surreptitiously hidden in the noise,
hence allowing the devices to operate indefinitely like hidden spies, apparently complying with security tests, and
producing only data in the form the protocols require,
but nonetheless actually eventually leaking all the purportedly secure data.
We stress that our results certainly do not imply that
quantum key distribution per se is insecure or impractical. In particular, our attacks do not apply to standard
QKD protocols in which the devices’ properties are fully
trusted, nor if the devices are trusted to be memoryless
(but otherwise untrusted), nor necessarily to protocols
relying on some other type of partially trusted devices.
Our target is the possibility of (full) device-independent
quantum cryptographic security, applicable to users who
purchase devices from a potentially sophisticated adversarial supplier and rely on no assumption about the devices’ internal workings.
The attacks we present raise new issues of composability and point towards the need for new protocol designs.
We discuss some countermeasures to our attacks that appear effective in the restricted but relevant scenario where
two users only ever use their devices for QKD exchanges
with one another, and propose a new type of protocol
that aims to achieve security in this scenario while allowing device reuse. Even with these countermeasures,
however, we show that security of a key generated with
Bob can be compromised if Alice uses the same device for
key generation with an additional party. This appears to
be a generic problem against which we see no complete
defence.
Although we focus on device-independent QKD for
most of this work, our attacks also apply to other deviceindependent quantum cryptographic tasks. The case of
randomness expansion is detailed in Appendix E.
Cryptographic scenario.—We use the standard cryptographic scenario for key distribution between Alice and
Bob, each of whom has a secure laboratory. These laboratories may be partitioned into secure sub-laboratories,
and we assume Alice and Bob can prevent communication between their sub-laboratories as well as between
their labs and the outside world, except as authorized by
the protocol. The setup of these laboratories is as follows.
Each party has a trusted private random string, a trusted
classical computer and access to two channels connecting
them. The first channel is an insecure quantum channel.
Any data sent down this can be intercepted and modified by Eve, who is assumed to know the protocol. The
second is an authenticated classical channel which Eve
can listen to but cannot impersonate; in efficient QKD
protocols this is typically implemented by using some
key bits to authenticate communications over a public
channel. Each party also uses a sub-laboratory to isolate
each of the untrusted devices being used for today’s protocol. They can connect them to the insecure quantum
channel, as desired, and this connection can be closed
thereafter. They can also interact with each device classically, supplying inputs (chosen using the trusted private
string) and receiving outputs, without any other information flowing into or out of the secure sub-laboratory.
As mentioned before, existing device-independent
QKD protocols that have been proven unconditionally
secure [6, 11, 12] require separate devices for each measurement performed by Alice and Bob with no possibility
of signalling between these devices[2], or are inefficient [17]
(in terms of the amount of key per entangled pair). For
practical device-independent QKD, we would like to remove both of these disadvantages and have an efficient
scheme needing a small number of devices.
Since the protocols in [11, 12] can tolerate reasonable
levels of noise and are reasonably efficient, we look first
at implementations of protocols taking the form of those
in [11, 12], except that Alice and Bob use one measurement device each, i.e., Alice (Bob) uses the same device to perform each of her (his) measurements. We call
these two-device protocols (Bob also has a separate isolated source device: see below). The memory of a device
can then act as a signal from earlier to later measurements, hence the security proofs of [11, 12] do not apply
(see also [20] where a different two-device setup is dis
2 Within the scenario described above, this could be achieved by
placing each device in its own sub-laboratory.
-----
1. Entangled quantum states used in the protocol are generated by a device Bob holds (which is separate and
kept isolated from his measurement device) and then
shared over an insecure quantum channel with Alice’s
device. Bob feeds his half of each state to his measurement device. Once the states are received, the quantum
channel is closed.
2. Alice and Bob each pick a random input Ai and Bi to
their device, ensuring they receive an output bit (Xi
and Yi respectively) before making the next input (so
that the i-th output cannot depend on future inputs).
They repeat this M times.
3. Either Alice or Bob (or both) publicly announces their
measurement choices, and the relevant party checks
that they had a sufficient number of suitable input combinations for the protocol. If not, they abort.
4. (Sifting.) Some output pairs may be discarded according to some public protocol.
5. (Parameter estimation.) Alice randomly and independently decides whether to announce each remaining bit
to Bob, doing so with probability µ (where Mµ ≫ 1).
Bob uses the communicated bits and his corresponding
outputs to compute some test function, and aborts if it
lies outside a desired range. (For example, Bob might
compute the CHSH value [21] of the announced data,
and abort if it is below 2.5.)
6. (Error correction.) Alice and Bob perform error correction using public discussion, in order to (with high
probability) generate identical strings. Eve learns the
error correction function Alice applies to her string.
7. (Privacy amplification.) Alice and Bob publicly perform privacy amplification [22], producing a shorter
shared string about which Eve has virtually no information. Eve similarly learns the privacy amplification
function they apply to their error-corrected strings.
TABLE I: Generic structure of the protocols we consider. Although this structure is potentially restrictive, most
protocols to date are of this form (we discuss modifications
later). Note that we do not need to specify the precise subprotocols used for error correction or privacy amplification.
For an additional remark, see Part I of the Appendix
cussed). It is an open question whether a secure key can
be efficiently generated by a protocol of this type in this
scenario. Here we demonstrate that, even if a key can be
securely generated, repeat implementations of the protocol using the same devices can render an earlier generated
key insecure.
Attacks on two-device protocols.—Consider a QKD protocol with the standard structure shown in Table I. We
imagine a scenario in which a protocol of this type is
run on day 1, generating a secure key for Alice and Bob,
while informing Eve of the functions used by Alice for error correction and privacy amplification (for simplicity we
assume the protocol has no sifting procedure (Step 4)).
The protocol is then rerun on day 2, to generate a second
key, using the same devices. Eve can instruct the devices
to proceed as follows. On day 1, they follow the protocol
honestly. However, they keep hidden records of all the
raw bits they generate during the protocol. At the end
of day 1, Eve knows the error correction and privacy amplification functions used by Alice and Bob to generate
the secure key.
On day 2, since Eve has access to the insecure quantum channel over which the new quantum states are distributed, she can surreptitiously modulate these quantum states to carry new classical instructions to the device in Alice’s lab, for example using additional degrees of
freedom in the states. These instructions tell the device
the error correction and privacy amplification functions
used on day 1, allowing it to compute the secret key generated on day 1. They also tell the device to deviate
from the honest protocol for randomly selected inputs,
by producing as outputs specified bits from this secret
key. (For example, “for input 17, give day 1’s key bit 5
as output”.) If any of these selected outputs are among
those announced in Step 5, Eve learns the corresponding
bits of day 1’s secret key. We call this type of attack, in
which Eve attempts to gain information from the classical
messages sent in Step 5, a parameter estimation attack.
If she follows this cheating strategy for Nµ[−][1] < M input bits, Eve is likely to learn roughly N bits of day 1’s
secret key. Moreover, only the roughly N output pairs
from this set that are publicly compared give Alice and
Bob statistical information about Eve’s cheating. Alice
and Bob cannot a priori identify these cheating output
pairs among the ≈ µM they compare. Thus, if the tolerable noise level is comparable to Nµ[−][1]M [−][1], Eve can (with
high probability) mask her cheating as noise. (Note that
in unconditional security proofs it is generally assumed
that eavesdropping is the cause of all noise. Even if in
practice Eve cannot reduce the noise to zero, she can
supply less noisy components than she claims and use
the extra tolerable noise to cheat).
In addition, Alice and Bob’s devices each separately
have the power to cause the protocol to abort on any
day of their choice. Thus – if she is willing to wait long
enough – Eve can program them to communicate some
or all information about their day 1 key, for instance
by encoding the relevant bits as a binary integer N =
b1 . . . bm and choosing to abort on day (N + 2)[3]. We call
this type of attack an abort attack. Note that it cannot
be detected until it is too late.
As mentioned above, some well known protocols use
many independent and isolated measurement devices.
These protocols are also vulnerable to memory attacks,
as explained in Appendix D.
3 In practice, Eve might infer a day (N +2) abort from the fact that
Alice and Bob have no secret key available on day (N +2), which
in many scenarios might detectably affect their behaviour then
or subsequently. Note too that she might alternatively program
the devices to abort on every day from (N + 2) onwards if this
made N more easily inferable in practice.
-----
Modified protocols.—We now discuss ways in which these
attacks can be partly defended against.
Countermeasure 1.—All quantum data and all public
communication of output data in the protocol come from
one party, say Bob. Thus, the entangled states used in
the protocol are generated by a separate isolated device
held by Bob (as in the protocol in Table 1) and Bob
(rather than Alice) sends selected output data over a
public channel in Step 5. If Bob’s device is forever kept
isolated from incoming communication, Eve has no way
of sending it instructions to calculate and leak secret key
bits from day 1 (or any later day).
Existing protocols modified in this way are still insecure if reused, however. For example, in a modified parameter estimation attack, Eve can pre-program Bob’s
device to leak raw key data from day 1 via output data
on subsequent days, at a low enough rate (compared to
the background noise level) that this cheating is unlikely
to be detected. If the actual noise level is lower than the
level tolerated in the protocol, and Eve knows both (a
possibility Alice and Bob must allow for), she can thereby
eventually obtain all Bob’s raw key data from day 1, and
hence the secret key.
In addition, Eve can still communicate with Alice’s
device, and Alice needs to be able to make some public
communication to Bob, if only to abort the protocol. Eve
can thus obtain secret key bits from day 1 on a later day
using an abort attack.
Countermeasure 2. [23] —Encrypt the parameter estimation information sent in Step 5 with some initial preshared seed randomness. Provided the seed required
is small compared to the size of final string generated
(which is the case in efficient QKD protocols [11, 12]),
the protocol then performs key expansion[4]. Furthermore,
even if they have insufficient initial shared key to encrypt the parameter estimation information, Alice and
Bob could communicate the parameter estimation information unencrypted on day 1, but encrypt it on subsequent days using generated key.
Note that this countermeasure is not effective against
abort attacks, which can now be used to convey all or
part of their day 1 raw key. This type of attack seems
unavoidable in any standard cryptographic model requiring composability and allowing arbitrarily many device
reuses if either Alice or Bob has only a single measurement device.
This countermeasure is also not effective in general cryptographic environments involving communication with multiple users who may not all be trustworthy. Suppose that Alice wants to share key with Bob on
day 1, but with Charlie on day 2. If Charlie becomes
corrupted by Eve, then, for example by hiding data in
4 QKD is often referred to as quantum key expansion in any case,
taking into account that a common method of authenticating the
classical channel uses pre-shared randomness.
the parameter estimation, Eve can learn about day 1’s
key (we call this an impostor attack ). This attack applies in many scenarios in which users might wish to use
device-independent QKD. For example, suppose Alice is
a merchant and Bob is a customer who needs to communicate his credit card number to Alice via QKD to
complete the sale. The next day, Eve can pose as a customer, carry out her own QKD exchange with Alice, and
extract information about Bob’s card number without
being detected.
Countermeasure 3.—Alternative protocols using additional measurement devices. Suppose Alice and Bob
each have m measurement devices, for some small integer
m ≥ 2. They perform Steps 1–6 of a protocol that takes
the form given in Table I but with Countermeasures 1
and 2 applied. They repeat these steps for each of their
devices in turn, ensuring no communication between any
of them (i.e., they place each in its own sub-laboratory).
This yields m error-corrected strings. Alice and Bob concatenate their strings before performing privacy amplification as in Step 7. However, they further shorten the
final string such that it would (with near certainty) remain secure if one of the m error-corrected strings were
to become known to Eve through an abort attack. (See
Table 2, and Appendix C for more details).
This countermeasure doesn’t avoid impostor attacks.
Instead, the idea is to prevent useful abort attacks (as
well as parameter estimation attacks due to Countermeasure 2), and hence give us a secure and composable
protocol, provided the keys produced on successive days
are always between the same two users. The information
each device has about day 1’s key is limited to the raw
key it produced. Thus, if each device is programmed to
abort on a particular day that encodes their day 1 raw
key, after an abort, Eve knows one of the devices’ raw
keys and has some information on the others (since she
can exclude certain possibilities based on the lack of abort
by those devices so far). After an abort, Alice and Bob
should cease to use any of their devices unless and until
such time that they no longer require that their keys remain secret. Intuitively, provided the set of m keys was
sufficiently shortened in the privacy amplification step,
Eve has essentially no information about the day 1 secret key, which thus (we conjecture) remains secure.
Countermeasure 4.—Alice and Bob share a small initial
secret key and use part of it to choose the privacy amplification function in Step 7 of the protocol, which may
then never become known to Eve.
Even in this case, Eve can pre-program Bob’s measurement device to leak raw data from day 1 on subsequent
days, either via a parameter estimation attack or via an
abort attack. While Eve cannot obtain bits of the secret key so directly in this case, provided the protocol
is composed sufficiently many times, she can eventually
obtain all the raw key. This means that Alice and Bob’s
residual security ultimately derives only from the initial
shared secret key: their QKD protocol produces no extra
permanently secure data.
-----
In summary, we have shown how a malicious manufacturer who wishes to mislead users or obtain data
from them can equip devices with a memory and use
it in programming them. The full scope of this threat
seems to have been overlooked in the literature on deviceindependent quantum cryptography to date. A task is
potentially vulnerable to our attacks if it involves secret
data generated by devices and if Eve can learn some function of the device outputs in a subsequent protocol. Since
even causing a protocol to abort communicates some information to Eve, the class of tasks potentially affected is
large indeed. In particular, for one of the most important
applications, QKD, none of the protocols so far proposed
remain composably secure in the case that the devices
are supplied by a malicious adversary.
One can think of the problems our attacks raise as
a new issue of cryptographic composability. One way
of thinking of standard composability is that a secure
output from a protocol must still have all the properties of an ideal secure output when combined with other
outputs from the same or other protocols. The deviceindependent key distribution protocols we have examined
fail this test because the reuse of devices can cause later
outputs to depend on earlier ones. In a sense, the underlying problem is that the usage of devices is not composably secure. This applies too, of course, for devices
used in different protocols: devices used for secure randomness expansion cannot then securely be used for key
distribution without potentially compromising the generated randomness, for example.
It is worth reiterating that our attacks do not apply
against protocols where the devices are trusted to be
memoryless. Indeed, there are schemes that are composably secure for memoryless devices [11, 12]. We also
stress that our attacks do not apply to all protocols for
device-independent quantum tasks related to cryptography. For example, even devices with memories cannot
mimic nonlocal correlations in the absence of shared entanglement [24, 25]. In addition, in applications that
require only short-lived secrets, devices may be reused
once such secrets are no longer required. Partially secure device-independent protocols for bit commitment
and coin tossing [19], in which the committer supplies
devices to the recipient, are also immune from our attacks, so long as the only data entering the devices come
from the committer.
Note too that, in practice the number of uses required
to apply the attacks may be very large, for example, in
the case of some of the abort attacks we described. One
can imagine a scenario in which Alice and Bob want to
carry out device-independent QKD no more than n times
for some fixed number n, each is confident in the other’s
trustworthiness throughout, the devices are used for no
other purpose and are destroyed after n rounds, and key
generation is suspended and the devices destroyed if a
single abort occurs. If the only relevant information con
veyed to Eve is that an abort occurs on one of the n days,
she can only learn at most log n bits of information about
the raw key via an abort attack. Hence one idea is that,
using suitable additional privacy amplification, Alice and
Bob could produce a device-independent protocol using
two measurement devices that is provably secure when
restricted to no more than n bilateral uses. It would be
interesting to analyse this possibility, which, along with
the protocol presented in Table 2, leads us to hold out
the hope of useful security for fully device-independent
QKD, albeit in restricted scenarios.
We have also discussed some possible defences and
countermeasures against our attacks. A theoretically
simple one is to dispose of – i.e. securely destroy or isolate
– untrusted devices after a single use (see Appendix B).
While this would restore universal composability, it is
clearly costly and would severely limit the practicality
of device-independent quantum cryptography. Another
interesting possibility is to design protocols for composable device-independent QKD guaranteed secure in more
restricted scenarios. However, the impostor attacks described above appear to exclude the possibility of composably secure device-independent QKD when the devices are used to exchange key with several parties.
Many interesting questions remain open. Nonetheless,
the attacks we have described merit a serious reappraisal
of current protocol designs and, in our view, of the practical scope of universally composable quantum cryptography using completely untrusted devices.
Added Remark: Since the first version of this paper,
there has been new work in this area that, in part, explores countermeasure 2 in more detail [26]. In addition,
two new works on device-independent QKD with only
two devices have appeared [27, 28]. Note that these do
not evade the attacks we present, but apply to the scenario where used devices are discarded.
Acknowledgements.—We thank Anthony Leverrier and
Gonzalo de la Torre for [23], Llu´ıs Masanes, Serge Massar and Stefano Pironio for helpful comments. JB was
supported by the EPSRC, and the CHIST-ERA DIQIP
project. RC acknowledges support from the Swiss National Science Foundation (grants PP00P2-128455 and
20CH21-138799) and the National Centre of Competence
in Research ‘Quantum Science and Technology’. AK was
partially supported by a Leverhulme Research Fellowship, a grant from the John Templeton Foundation, and
the EU Quantum Computer Science project (contract
255961). This research is supported in part by Perimeter
Institute for Theoretical Physics. Research at Perimeter Institute is supported by the Government of Canada
through Industry Canada and by the Province of Ontario
through the Ministry of Research and Innovation.
-----
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Appendix A: Separation of sources and
measurement devices
We add here one important comment about the general structure of the generic protocol given in Table 1 of
the main text. There it was crucial that in Step 1, in the
-----
case where Bob (rather than Eve) supplies the states, he
does so using a device that is isolated from his measurement device. If, on the other hand, Bob had only a single
device that both supplies states and performs measurements, then his device can hide information about day 1’s
raw key in the states he sends on day 2. (This can be
done using states of the form specified in the protocol,
masking the errors as noise as above. Alternatively, the
data could be encoded in the timings of the signals or in
quantum degrees of freedom not used in the protocol.)
Appendix B: Toxic device disposal
As noted in the main text, standard cryptographic
models postulate that the parties can create secure
laboratories, within which all operations are shielded
from eavesdropping. Device-independent quantum cryptographic models also necessarily assume that devices
within these laboratories cannot signal to the outside
– otherwise security is clearly impossible. Multi-device
protocols assume that the laboratories can be divided
into effectively isolated sub-laboratories, and that devices in separate sub-laboratories cannot communicate.
In other words, Alice and Bob must be able to build arbitrary configurations of screening walls, which prevent
communication among Eve and any of her devices, and
allow only communications specified by Alice and Bob.
Given this, there is no problem in principle in defining
protocols which prescribe that devices must be permanently isolated: the devices simply need to be left indefinitely in a screened sub-laboratory. While this could be
detached from the main working laboratory, it must be
protected indefinitely: screening wall material and secure
space thus become consumed resources. And indeed in
some situations, it may be more efficient to isolate devices, rather than securely destroy them, since devices
can be reused once the secrets they know have become
public by other means. For example, one may wish to
securely communicate the result of an election before announcing it, but once it is public, the devices used for
this secure communication could be safely reused.
The alternative, securely destroying devices and then
eliminating them from the laboratory, preserves laboratory space but raises new security issues: consider, for example, the problems in disposing of a device programmed
to change its chemical composition depending on its output bit.
That said, no doubt there are pretty secure ways of
destroying devices, and no doubt devices could be securely isolated for long periods. However, the costs and
problems involved, together with the costs of renewing
devices, make us query whether these are really viable
paths for practical device-independent quantum cryptography.
Appendix C: Privacy Amplification
Here we briefly outline the important features of privacy amplification, which is a key step in the protocol. As
explained in the main text, the idea is to compress the
string such that (with high probability) an eavesdropper’s knowledge is reduced to nearly zero. This usually
works as follows. Suppose Alice and Bob share some random string, X, which may be correlated with a quantum
system, E, held by the eavesdropper. Alice also holds
some private randomness, R. The state held by Alice
and Eve then takes the form
�
ρXRE = PX (x)PR(r)|x⟩⟨x|X ⊗|r⟩⟨r|R ⊗ ρ[x]E[,]
x,r
where {ρ[x]E[}][x][ are normalized density operators, and]
PR(r) = 1/|R|. The randomness R is used to choose
a function fR ∈F, where F is some suitably chosen
set, to apply to X such that, even if she learns R, the
eavesdropper’s knowledge about the final string is close
to zero. If we call the final string S = fR(X), then Eve
has no knowledge about it if the final state takes the form
τS ⊗ ρRE, where τS is maximally mixed on S. However,
we cannot usually attain such a state, and instead measure the success of a protocol by its variation from this
ideal, measured using the trace distance, D. Denoting
the final state (after applying the function) by ρSRE, we
are interested in D(ρSRE, τS ⊗ ρRE).
Fortunately, several sets of function are known for
which the above distance can be made arbitrarily small.
Two common constructions are those based on twouniversal hash functions [3, 29–31] and Trevisan’s extractor [32, 33]. The precise details of these is not very important for the present work (we refer the interested reader
to the references), nor is it important which we choose.
However, it is worth noting that for two-universal hash
functions, the size of the seed needs to be roughly equal
to that of the final string, while for Trevisan’s extractor, this can be reduced to roughly the logarithm of the
length of the initial string (in the latter case, this may
allow it to be sent privately, if desired).
For both, the amount that the string should be compressed is quantified by the smooth conditional minentropy, which we now define. For a state ρAB, the nonsmooth conditional min-entropy is defined as
Hmin(A|B)ρ := max
σB [sup][{][λ][ ∈] [R][ : 2][−][λ][1][1][A][ ⊗] [σ][B][ ≥] [ρ][AB][}][,]
in terms of which the smooth min entropy is given by
Hmin[ε] [(][A][|][B][)][ρ][ := max]ρ¯AB [H][min][(][A][|][B][)][ρ][¯][.]
The maximization over ¯ρ is over a set of states that are
close to ρAB according to some distance measure (see,
for example, [34] for a discussion).
The significance for privacy amplification can be seen
as follows. In [3], it is shown that if f is chosen randomly
from a set of two-universal hash functions, and applied
-----
1. Entangled quantum states used in the protocol are generated by a device Bob holds (which is separate and
kept isolated from his measurement devices) and then
shared over an insecure quantum channel with Alice’s
first device. Bob feeds his half of each state to his first
measurement device. Once the states are received, the
quantum channel is closed.
2. Alice and Bob each pick a random input Ai and Bi
to their first device, ensuring they receive an output
bit (Xi and Yi respectively) before making the next
input (so that the i-th output cannot depend on future
inputs). They repeat this M times.
3. Bob publicly announces his measurement choices, and
Alice checks that for a sufficient number of suitable input combinations for the protocol. If not, Alice aborts.
4. (Sifting.) Some output pairs may be discarded according to some protocol.
5. (Parameter estimation.) Alice and Bob use their preshared key to randomly select some output pairs (they
select only a small fraction, hence the amount of key
required for this is small). For each of the selected
pairs, Bob encrypts his output and sends it to Alice.
Alice uses the communicated bits and her corresponding outputs to compute some test function, and aborts
if it lies outside a desired range.
6. (Error correction.) Alice and Bob perform error correction using public discussion, in order to (with high
probability) generate identical strings. Eve learns the
error correction function Alice applies to her string.
7. Alice and Bob repeat Steps 1–6 for each of their
m devices (ensuring the devices cannot communicate
throughout)
8. (Privacy amplification.) Alice and Bob concatenate
their m strings and publicly perform privacy amplification [22], producing a shorter shared string about
which Eve has virtually no information. In this step,
the size of their final string is chosen such that (with
high probability) it will remain secure even if one of
the raw strings or its error corrected version becomes
known.
TABLE 2: Structure of the protocol from the main
text with modifications as in Countermeasure 3. For
this protocol Alice and Bob each have m ≥ 2 measurement
devices, and Bob has one device for creating states. They are
all kept isolated from one another.
to the raw string X, as above, then for |S| = 2[t] and any
ε ≥ 0,
D(ρSRE, τS ⊗ ρRE) ≤ ε + [1] 2 [(][H]min[ε] [(][X][|][E][)][−][t][)].
2 [2][−] [1]
(An analogous statement can be made for Trevisan’s extractor [33].) Thus, if Alice compresses her string to
length t = Hmin[ε] [(][X][|][E][)][ −] [ℓ][, then the final state after ap-]
plying the hash function has distance ε + [1]2 [2][−][ℓ/][2][ to a]
state about which Eve has no knowledge.
Turning to the QKD protocol in Table 1 of the main
text, in the case of hashing the privacy amplification procedure consists of Alice selecting t depending on the test
function computed in the parameter estimation step. She
then uses local randomness to choose a hash function to
apply to her string, and announces this to Bob, who applies the same function to his string (since we have already performed error correction, this string should be
identical to Alice’s). The idea is that, if t is chosen appropriately, it is virtually impossible that the parameter
estimation tests pass and the final state at the end of
the protocol is not close to one for which Eve has no
knowledge about the final string.
In the modified protocol in Table 2, we expect each
pair of devices to contribute roughly the same amount of
smooth min entropy to the concatenated string. Thus,
since there are m devices, in order to tolerate the potential revelation of one of the error-corrected strings
through an abort attack, Alice should choose t to be
roughly (m − 1)/m shorter than she would otherwise.
Appendix D: Memory attacks on multi-device QKD
protocols
To illustrate further the generality of our attacks, we
now turn to multi-device protocols, and show how to
break iterated versions of two well known protocols.
Attacks on compositions of the BHK protocol
The Barrett-Hardy-Kent (BHK) protocol [6] requires
Alice and Bob to share MN [2] pairs of systems (where
M and N are both large with M ≪ N ), in such a
way that no measurements on any subset can effectively
signal to the others. In a device-independent scenario,
we can think of these as black box devices supplied by
Eve, containing states also supplied by Eve. Each device is isolated within its own sub-laboratory of Alice’s
and Bob’s, so that Alice and Bob have MN [2] secure sublaboratories each. The devices accept integer inputs in
the range {0, . . ., N − 1} and produce integer outputs in
the range {0, 1}. Alice and Bob choose random independent inputs, which they make public after obtaining all
the outputs. They also publicly compare all their outputs
except for those corresponding to one pair randomly chosen from among those in which the inputs differ by ±1
or 0 modulo N . If the publicly declared outputs agree
with quantum statistics for specified measurement basis
choices (corresponding to the inputs) on a singlet state,
then they accept the protocol as secure, and take the
final undeclared outputs (which are almost certainly anticorrelated) to define their shared secret bit.
The BHK protocol produces (with high probability)
precisely one secret bit: evidently, it is extremely inefficient in terms of the number of devices required. It
also requires essentially noise-free channels and errorfree measurements. Despite these impracticalities it il
-----
lustrates our theoretical point well. Suppose that Alice
and Bob successfully complete a run of the BHK protocol
and then (unauthorised by BHK) decide to use the same
2MN [2] devices to generate a second secret bit, and ask
Eve to supply a second batch of states to allow them to
do this.
Eve — aware in advance that the devices may be
reused — can design them to function as follows. In
the first run of the protocol, she supplies a singlet pair
to each pair of devices and the devices function honestly,
carrying out the appropriate quantum measurements on
their singlets and reporting the outcomes as their outputs. However, they also store in memory their inputs
and outputs. In the second run, Eve supplies a fresh
batch of singlet pairs. However, she also supplies a hidden classical signal identifying the particular pair of devices that generated the first secret bit. (This signal need
go to just one of this pair of devices, and no others.) On
the second run, the identified device produces as output
the same output that it produced on the first run (i.e. the
secret bit generated, up to a sign convention known to
Eve). All other devices function honestly on the second
run.
With probability [MN]MN[ 2][−][2][, the output from the cheating][1]
device on the second run will be made public, thus revealing the first secret bit to Eve. Moreover, with probability
1 − 23N [+][ O][(][N][ −][2][), this cheating will not be detected by]
Alice and Bob’s tests, so that Eve learns the first secret
bit without her cheating even being noticed.
There are defences against this specific attack. First,
the BHK protocol [6] can be modified so that only outputs corresponding to inputs differing by ±1 or 0 are
publicly shared.[5] While this causes Eve to wait many
rounds for the secret bit to be leaked, and increases the
risk her cheating will be detected, it leaves the iterated
protocol insecure. Second, Alice and Bob could securely
destroy or isolate the devices producing the secret key
bit outputs, and reuse all their other devices in a second
implementation. Since only the devices generating the
secret key bit have information about it, this prevents it
from being later leaked. While effective, this last defence
really reflects the inefficiency of the BHK protocol: to illustrate this, we turn next to a more efficient multi-device
protocol.
Attacks on compositions of the HR protocol
H¨anggi and Renner (HR) [11] consider a multi-device
QKD protocol related to the Ekert [2] protocol, in which
Alice and Bob randomly and independently choose one of
5 As originally presented, the BHK protocol requires public exchange of all outputs except those defining the secret key bit.
This is unnecessary, and makes iterated implementations much
more vulnerable to the attacks discussed here.
two or three inputs respectively for each of their devices.
If the devices are functioning honestly, these correspond
to measurements of a shared singlet in the bases U0, U1
(Alice) and V0, V1, V2 (Bob), defined by the following vectors and their orthogonal complements
U1 ↔|0⟩,
V0 ↔ cos(π/8)|0⟩ + sin(π/8)|1⟩,
U0, V2 ↔ cos(π/4)|0⟩ + sin(π/4)|1⟩,
V1 ↔ cos(3π/8)|0⟩ + sin(3π/8)|1⟩ .
The raw key on any given run is defined by the ≈ 1/6
of the cases in which U0 and V2 are chosen. Information
reconciliation and privacy amplification proceed according to protocols of the type described in the main text
(in which the functions used are released publicly).
Evidently, our attacks apply here too if (unauthorised
by HR) the devices are reused to generate further secret
keys. Eve can identify the devices that generate the raw
key on day 1, and request them to release their key as
cheating outputs on later days, gradually enough that the
cheating will be lost in the noise. Since the information
reconciliation and privacy amplification functions were
made public by Alice, she can then obtain the secret key.
Even if she is unable to communicate directly with the
devices for a long time (because they were pre-installed
with a very large reservoir of singlets), she can program
all devices to gradually release their day 1 outputs over
subsequent days, and so can still deduce the raw and
secret keys.
Alice and Bob could counter these attacks by securely
destroying or isolating all the devices that generated raw
key on day 1 — but this costs them 1/6 of their devices,
and they have to apply this strategy each time they generate a key, leaving (5/6)[N] of the devices after N runs,
and leaving them able to generate shorter and shorter
keys. As the length of secure key generated scales by
(5/6)[N] (or worse, allowing for fluctuations due to noise)
on each run, the total secret key generated is bounded
by ≈ 6M, where M is the secret key length generated on
day 1.
Note that, as in the case of the iterated BHK protocol, all devices that generate secret key become toxic and
cannot be reused. While the relative efficiency of the HR
protocol ensures a (much) faster secret key rate, it also
requires an equally fast device depletion rate. This example shows that our attacks pose a generic problem for
device-independent QKD protocols of the types considered to date.
Appendix E: Device-independent randomness
expansion protocols: attacks and defences
Device-independent quantum randomness expansion
(DVI QRE) protocols were introduced by two of us [13,
15], developed further by [14, 35–37], and there now exist schemes with unconditional security proofs [36]. The
-----
cryptographic scenario here is slightly different from that
of key distribution in that there is only one honest party,
Alice.
Alice’s aim is to expand an initial secret random string
to a longer one that is guaranteed secret from an eavesdropper, Eve, even if the quantum devices and states
used are supplied by Eve. The essential idea is that seed
randomness can be used to carry out nonlocality tests on
the devices and states, within one or more secure laboratories, in a way that guarantees (with numerical bounds)
that the outcomes generate a partially secret and random string. Privacy amplification can then be used to
generate an essentially fully secret random string, which
(provided the tests are passed) is significantly longer than
the initial seed.
There are already known pitfalls in designing such protocols. For example, although one might think that carrying out a protocol in a single secure laboratory guarantees that the initially secure seed string remains secure,
and so guarantees randomness expansion if any new secret random data is generated, this is not the case [15].
Eve’s devices may be programmed to produce outputs depending on the random seed in such a way that the length
of the final secret random string depends on the initial
seed. Protocols with this vulnerability are not composably secure. (To see this can be a practical problem, note
that Eve may infer the length of the generated secret random string from its use.)
A corollary of our results is that, if one wants to reuse
the devices to generate further randomness, it is crucial
to carry out DVI QRE protocols with devices permanently held within a single secure laboratory, avoiding
any public communication of device output data at any
stage. It is crucial too that the devices themselves are securely isolated from classical communications and computations within the laboratory, to prevent them from
learning details of the reconciliation and privacy amplification.
Even under these stringent conditions, our attacks still
apply in principle. For example, consider a noise-tolerant
protocol that produces a secret random output string of
variable length, depending on the values of test functions
of the device outputs (the analogue of QKD parameter
estimation for QRE) that measure how far the device
outputs deviate from ideal honest outputs. This might
seem natural for any single run, since – if the devices are
never reused – the length of the provably secret random
string that can be generated does indeed depend on the
value of a suitable test function. However, iterating such
a protocol allows the devices to leak information about
(at least) their raw outputs on the first run by generating
artificial noise in later rounds, with the level of extra
noise chosen to depend suitably on the output values.
Such noise statistically affects the length of the output
random strings on later rounds.
In this way, suitably programmed devices could ultimately allow Eve to infer all the raw outputs from the
first round, given observation of the key string lengths
created in later rounds. This makes the round one QRE
insecure, since given the raw outputs for round one, and
knowing the protocol, Eve knows all information about
the output random string for round one, except that determined by the secret random seed.
One defence against this would be to fix a length L for
the random string generated corresponding to a maximum acceptable noise level, and then to employ the Procrustean tactic of always reducing the string generated
to length L, regardless of the measured noise level.
Even then, though, unless some restriction is placed on
the number of uses, the abort attack on QKD protocols
described in the main text also applies here. The devices
have the power to cause the protocol to abort on any
round of their choice, and so – if she is willing to wait
long enough – Eve can program them to communicate
any or all information about their round 1 raw outputs
by choosing the round on which they cause an abort.
We also described in the main text a moderately costly
but apparently effective defence against abort attacks
on QKD protocols, in which Alice and Bob each have
several isolated devices that independently generate raw
sub-keys, which are concatenated and privacy amplified so that exposing a single sub-key does not significantly compromise the final secret key. This defence appears equally effective against abort attacks on deviceindependent quantum randomness expansion protocols.
Since quantum randomness expansion generally involves
only a single party, these protocols are not vulnerable to
the impostor attacks described in the main text. It thus
appears that it may be possible in principle to completely
defend them against memory attacks, albeit at some cost.
It is also worth noting that there are many scenarios in which one only needs short-lived randomness, for
example, in many gambling applications, bets are often
placed about random data that are later made public.
In such scenarios, once such random data have been revealed, the devices could be reused without our attacks
presenting any problem.
-----
| 13,355
|
{
"disclaimer": "Notice: Paper or abstract available at https://arxiv.org/abs/1201.4407, which is subject to the license by the author or copyright owner provided with this content. Please go to the source to verify the license and copyright information for your use.",
"license": null,
"status": "GREEN",
"url": "http://arxiv.org/pdf/1201.4407"
}
| 2,012
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[
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| 2012-01-20T00:00:00
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{
"paperId": "17c16c133ab46e66ea0a08f40d19b3308733c348",
"title": "Quantum cryptography: Public key distribution and coin tossing"
},
{
"paperId": "da3de28bfd3019d84c3c5fb54922cfa36b683484",
"title": "Reusing devices with memory in device independent quantum key distribution"
},
{
"paperId": "9c4c1da0698b78dd664d144b813b595480641f1e",
"title": "Unconditionally secure device-independent quantum key distribution with only two devices"
},
{
"paperId": "e1469396f6ff2eb3ebd592e27db829306ba8b712",
"title": "Classical command of quantum systems via rigidity of CHSH games"
},
{
"paperId": "050b4e393f4629c1869d8b39b5c1904cf36540c0",
"title": "Security and Composability of Randomness Expansion from Bell Inequalities"
},
{
"paperId": "c6d2abf4806ba7a7c45251be8e27d8b6d916a014",
"title": "Certifiable Quantum Dice - Or, testable exponential randomness expansion"
},
{
"paperId": "fa16254cda21e31d45a9920983f65a8eab1201da",
"title": "Device-independent randomness expansion secure against quantum adversaries"
},
{
"paperId": "c0a216cc6060649ff7dbd8c6816f44ce02e31caa",
"title": "Fully distrustful quantum bit commitment and coin flipping."
},
{
"paperId": "aae169e6f13726343cf569b627a6ff958135b511",
"title": "Private randomness expansion with untrusted devices"
},
{
"paperId": "7fcb2d74ecde9506138d1835c7da51a1f010e1e5",
"title": "Full-field implementation of a perfect eavesdropper on a quantum cryptography system."
},
{
"paperId": "f3208f01ccfe7b5a89f53815faf7a37e2cb671e5",
"title": "Device-Independent Quantum Key Distribution with Commuting Measurements"
},
{
"paperId": "34c35806d493709645bbec0f400c72bf208d2c36",
"title": "Secure device-independent quantum key distribution with causally independent measurement devices."
},
{
"paperId": "0460303f7bac4fc8eae01482b31b2fb98bf9e95e",
"title": "Leftover Hashing Against Quantum Side Information"
},
{
"paperId": "34b71802dac3b478504b34d23483bd43fd558040",
"title": "Trevisan's Extractor in the Presence of Quantum Side Information"
},
{
"paperId": "14fdbdc3a57c072a8332826ab3291b6a8e664f3b",
"title": "Quantum And Relativistic Protocols For Secure Multi-Party Computation"
},
{
"paperId": "29dd7297102a2f248323aa5450ea7b3980180091",
"title": "Random numbers certified by Bell’s theorem"
},
{
"paperId": "edbd126301d391bc917add68527eede51260bd9f",
"title": "Less reality, more security"
},
{
"paperId": "d9745d2a4d5fa96fcfd44e6111c6129bd8c836ab",
"title": "Duality Between Smooth Min- and Max-Entropies"
},
{
"paperId": "be2e91a735e4084ea92439f517f4d31713472b0a",
"title": "Device-independent security of quantum cryptography against collective attacks."
},
{
"paperId": "e76bb6dec7591c18ddddc4a18e60574aaac07f9f",
"title": "Secrecy extraction from no-signaling correlations"
},
{
"paperId": "dea44b39d8b8d8cbf16730a53c2c00365a19a29b",
"title": "Maximally Non-Local and Monogamous Quantum Correlations"
},
{
"paperId": "022f4ca76b07470a6ef1824fa546e5b093a9fbf2",
"title": "Security of quantum key distribution"
},
{
"paperId": "57afbbf50de42a137c1ae2d815db3f65bd7f79b2",
"title": "From Bell's theorem to secure quantum key distribution."
},
{
"paperId": "fc5b6f804af3f5937de217e2064e0a00f4b31d79",
"title": "No signaling and quantum key distribution."
},
{
"paperId": "4d9f0580409beb76d3576cadce59168686d49b3a",
"title": "Quantum nonlocality, Bell inequalities, and the memory loophole"
},
{
"paperId": "95ea3854f3e6bbb72d914e12e7e85b34b89518f1",
"title": "Appendix to \"Accardi contra Bell (cum mundi) : The Impossible Coupling\""
},
{
"paperId": "142e66fa3d21519838d7a4907303b562ed2a2f71",
"title": "Quantum cryptography with imperfect apparatus"
},
{
"paperId": "f8dcc3047eef8da135bca13b926b1e6cf50e7f3a",
"title": "Quantum cryptography based on Bell's theorem."
},
{
"paperId": "47cd50eec7f3d5ba6e4db9afdd9ea83545674236",
"title": "A personal communication"
},
{
"paperId": "594dfbdf3e3ba9df94a31ab9cb1e23912773b98a",
"title": "Privacy Amplification by Public Discussion"
},
{
"paperId": "345e83dd58f26f51d75e2fef330c02c9aa01e61b",
"title": "New Hash Functions and Their Use in Authentication and Set Equality"
},
{
"paperId": "feb061b699a2249f803baf159a991d63c64f9c99",
"title": "Universal Classes of Hash Functions"
},
{
"paperId": "8864c5214a30a7acd8d186f53e8991cd8bc88f84",
"title": "Proposed Experiment to Test Local Hidden Variable Theories."
},
{
"paperId": null,
"title": "The impossibility of non-signalling privacy amplification"
},
{
"paperId": "ca73bec3f9b1a483c64ccb51e8dd154fe87fbd42",
"title": "Extractors and pseudorandom generators"
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"title": "Parameter estimation"
},
{
"paperId": null,
"title": "No Signalling and Quantum Key Distribution a Quantum Protocol for Secret Bit Distribution"
},
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"paperId": "fc60c0f724eb8436b9f10a530c27484b1c8be321",
"title": "Ju n 20 06 Unconditional security of key distribution from causality constraints"
},
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"title": "Bob publicly announces his measurement choices, and Alice checks that for a sufficient number of suitable input combinations for the protocol. If not"
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{
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https://www.semanticscholar.org/paper/0002c60ed10a8868930b8f971af29e62b498f6b8
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Problems of evaluation of digital evidence based on blockchain technologies
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JANUS NET e-journal of International Relation
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OBSERVARE
Universidade Autónoma de Lisboa
e-ISSN: 1647-7251
Vol. 14, Nº. 1 (May-October 2023)
# NOTES AND REFLECTIONS
PROBLEMS OF EVALUATION OF DIGITAL EVIDENCE BASED ON
BLOCKCHAIN TECHNOLOGIES[1]
**OTABEK PIRMATOV**
[[email protected]](mailto:[email protected])
Assistant Professor of the Department of Civil Procedural and Economic Procedural Law,
Tashkent State University of Law (Uzbekistan), Doctor of Philosophy in Law (PhD)
## Introduction
Digital evidence is fundamentally different from physical evidence and written evidence.
Securing physical evidence is primarily to prevent it from being lost or difficult to obtain
in the future.
Compared to traditional evidence, electronic evidence is fragile, easy to change and
delete, and difficult to guarantee its authenticity. For example, data on a personal
computer may be lost due to misuse, virus attack, etc. During the preparation of the
case, the video can be deleted in order to hide the facts. In fact, most electronic evidence
is stored in a central database. If the database is unreliable, the validity of the data is
not guaranteed. Obviously, how to ensure the authenticity and integrity of digital
evidence is very important when storing it.
Because digital evidence is created by special high-tech, it is easier to change it in
practice. More attention should be paid to its authenticity. Digital evidence is more likely
to be tampered with in practice.
The main methods of digital evidence storage (pre-trial provision) in civil court
proceedings are as follows:
1) sealing or closing the means of keeping the original of evidence;
2) printing, photographing and sound or visual recording;
1 This text is devoted the issues of evaluation of digital evidence based on blockchain technologies in civil
court proceedings. The article states that since it is not possible to change and delete evidence based on
block-chain technology, contracts based on blockchain technology and documents issued by government
bodies are considered acceptable evidence by the courts. It is highlighted that the usage of evidence based
on block-chain technology in conducting civil court cases will prevent the need for notarization of digital
evidence by the parties in the future.
-----
JANUS.NET, e journal of International Relations
e-ISSN: 1647-7251
Vol. 14, Nº. 1 (May-October 2023), pp. 279-288
_Notes and Reflections_
_Problems of evaluation of digital evidence based on blockchain technologies_
Otabek Pirmatov
3) drawing up reports;
4) authentication;
5) provision through a notary office;
6) storage through block-chain;
7) casting a time stamp (time stamp).
Block-chain is a database where data is securely stored. This is achieved by connecting
each new record with the previous one, resulting in a chain consisting of data blocks
("block chain" in English)—hence the name. Physically, the blockchain database is
distributed, allowing authorized users to independently add data. It is impossible to make
changes to previously stored data, as this action will break the chain, and it is
"immutability" that makes the block-chain a safe and reliable means of storing digital
records in public databases[2].
Officially, the history of “blocks and chains” begins on October 31, 2008, when someone
under the pseudonym Satoshi Nakamoto mentioned the blockchain in a white paper (base
document) about the network of the first cryptocurrency - bitcoin. The fundamental
principles for applying decentralization and immutability to document accounting were
laid down as early as the 1960s and 1970s, but the closest to them are the works of
scientists Stuart Haber and W. Scott Stornett, who in 1991 described a scheme for
sequentially creating blocks in which a hash is located. The technology was even
patented, but for its time it became a Da Vinci helicopter - there was no technical
possibility to implement the idea, and interest in it disappeared. The patent expired in
2004, just four years before Satoshi and his white paper appeared[3].
## 1. Literature review
S.S. Gulyamov defines block-chain as follows: blockchain (chain of blocks) is a distributed
set of data, in which data storage devices are not connected to a common server. These
data sets are called blocks and are stored in an ever-growing list of ordered records. Each
block will have a timestamp and a reference to the previous block. The use of encryption
ensures that users cannot write to the file without them, while the presence of private
keys can only modify a certain part of the blockchains.
In addition, encryption ensures synchronization of all users' copies of the distributed
chain of blocks (Gulyamov, 2019: 114).
Primavera De Filippi and Aaron Wright (2018) point out that block-chain technology is
different from other electronic evidence because it cannot be forgotten. The technology
itself has evidential value for the judicial system.
_Markus Kaulartz, Jonas Gross, Constantin Lichti, Philipp Sandner_ define block-chain
technology is getting increasingly renowned, as more and more companies develop
blockchain-based prototypes, e.g., in the context of payments, digital identities, and the
2 [https://www.gazeta.uz/uz/2022/08/26/blockchain-technology/](https://www.gazeta.uz/uz/2022/08/26/blockchain-technology/)
3 [https://www.forbes.ru/mneniya/456381-cto-takoe-blokcejn-vse-cto-nuzno-znat-o-tehnologii](https://www.forbes.ru/mneniya/456381-cto-takoe-blokcejn-vse-cto-nuzno-znat-o-tehnologii)
-----
JANUS.NET, e journal of International Relations
e-ISSN: 1647-7251
Vol. 14, Nº. 1 (May-October 2023), pp. 279-288
_Notes and Reflections_
_Problems of evaluation of digital evidence based on blockchain technologies_
Otabek Pirmatov
supply chain. One use case of blockchain is often seen in the tamper-proof storage of
information and documentation of facts. This is due to the fact that records on a blockchain are “practically resistant” to manipulation as a consequence of the underlying
cryptography and the consensus mechanism.
If a block-chain is used for storing information, the question arises whether the data stored
on a block-chain can be used as evidence in court. In the following article, we will analyze
this question[4].
According to Alexey Sereda, the correct usage of blockchain technologies will eliminate
the need for lawyers to perform certain mechanical tasks to a significant extent: checking
counterparties, contacting other experts (bodies), the need for notarization, etc. All this
allows lawyers to focus their efforts on solving other more important tasks[5].
Vivien Chan and Anna Mae Koo define blockchain is a decentralized and open distributed
ledger technology. Electronic data (e.g. in a transaction on an e-shopping platform, the
transaction time, purchase amount, currency and participants, etc.) will be uploaded to
a network of computers in “blocks”. Since the data saved in a blockchain is stored in a
network of computers in a specific form and is publicly available for anyone to view, the
data is irreversible and difficult to be manipulated.
Anyone who has handled an online infringement case knows the race against time in
preserving evidence. However, screenshots saved in PDF formats are easy to be
tampered with and are of scant probative value before the Chinese courts, unless
notarized. Making an appointment with, and appearing before a notary is another timeconsuming and expensive process.
With blockchain, these procedures can be simplified and improved in the following ways:
1. E-evidence can be saved as blockchain online instantaneously without a notary
public;
2. Cost for generating blockchain evidence is lower than traditional notarization;
3. Admissibility of block-chain evidence has been confirmed by statute and many courts
in China because of the tamper-free nature of block-chain technology;
4. Possible combination of online monitoring and evidence collection process: with
blockchain technology and collaboration with different prominent online platforms
(e.g. Weixin), it is possible to automate online monitoring of your intellectual
property—blockchain evidence is saved automatically when potential infringing
contents are found[6].
According to Matej Michalko, in the previous trials of dispute cases, evidence preservation
usually requires the involvement of a third-party authority such as a notary office, and
relevant persons are required to fix the evidence under the witness of the notary. With
the more frequent use of electronic evidence, most of the third-party electronic data
preservation platforms have investigated the pattern of “block-chain + evidence
4 [www.jonasgross.medium.com/legal-aspects-of-blockchain-technology-part-1-blockchain-as-evidence-in-](http://www.jonasgross.medium.com/legal-aspects-of-blockchain-technology-part-1-blockchain-as-evidence-in-court-704ab7255cf5)
[court-704ab7255cf5](http://www.jonasgross.medium.com/legal-aspects-of-blockchain-technology-part-1-blockchain-as-evidence-in-court-704ab7255cf5)
5 [https://blockchain24.pro/blokcheyn-i-yurisprudentsiya](https://blockchain24.pro/blokcheyn-i-yurisprudentsiya)
6 [https://www.lexology.com/library/detail.aspx?g=1631e87b-155a-40b4-a6aa-5260a2e4b9bb](https://www.lexology.com/library/detail.aspx?g=1631e87b-155a-40b4-a6aa-5260a2e4b9bb)
-----
JANUS.NET, e journal of International Relations
e-ISSN: 1647-7251
Vol. 14, Nº. 1 (May-October 2023), pp. 279-288
_Notes and Reflections_
_Problems of evaluation of digital evidence based on blockchain technologies_
Otabek Pirmatov
collection and preservation”, which is applying blockchain technology to the traditional
electronic evidence preservation practice (i.e., uploading the preserved evidence to a
block-chain platform). If it is necessary, you can apply online for an expert opinion from
the judicial expertise center. (Michalko, 2019: 7).
Today, the task of providing electronic evidence before the court is carried out by
notaries.
Data recorded on a blockchain is in essence a chronological chain of digitally signed
transactions. Thus, admissibility of block-chain evidence is highly correlated to
acceptance of electronic signatures in a legal setting. Not all electronic signatures provide
the same level of assurance. (Murray, 2016: 517-519).
The usage of this technology when concluding transactions or receiving any official
documents from the state greatly simplifies the process of proof, as it allows to track the
entire history of changes made to the information stored in the blockchain. It also reliably
protects them from illegal attempts to tamper or forge. Such evidence will be nearly
impossible to challenge, although the risk of hacking or fraudulent activity remains.
Second, if the court session is conducted using video conferencing, the blockchain can
be easily used by the participants in the court session. Given the development of remote
technologies caused by the coronavirus pandemic, this situation must be taken into
account. Thus, thanks to the use of blockchain, it is possible to significantly reduce the
time for consideration of cases in courts, increase the transparency of court proceedings
and ensure the necessary confidentiality of information.
If the contracts concluded by the parties are based on the blockchain technology or if the
state authorities draw up their documents based on the blockchain technology, then it
would be possible to evaluate the blockchain technology as evidence by the courts. Now
in our country, government bodies are signing their documents with Q-code.
According to Boris Glushenkov, the successful implementation of the blockchain will also
change the courts: firstly, there will be no need to make decisions for concrete things.
Second, evidence changes: electronic evidence is viewed with skepticism in courts.
Maybe blockchain can change that[7].
In civil litigation, evidence was evaluated as evidence only if it met each of the criteria of
relevance, admissibility, and reliability. Likewise, numerical evidence must meet the
requirements of relevance, acceptability, and reliability of evidence evaluation criteria.
Failure to evaluate digital evidence with one of the evidentiary evaluation criteria may
result in its inadmissibility as evidence in court.
According to Yuhei Okakita, In civil litigation, any form of evidence can generally be
submitted to the court. That is, the court accepts not only physical documents but also
digital data as evidence. Of course, civil procedure laws vary from country to country,
but electronic evidence is recognized in many legislations such as the EU, the United
States, or Japan. Since it can be said that blockchain certificates are a kind of digital
data, it should be accepted in most courts as admissible evidence.
7 [https://blockchain24.pro/blokcheyn-i-yurisprudentsiya](https://blockchain24.pro/blokcheyn-i-yurisprudentsiya)
-----
JANUS.NET, e journal of International Relations
e-ISSN: 1647-7251
Vol. 14, Nº. 1 (May-October 2023), pp. 279-288
_Notes and Reflections_
_Problems of evaluation of digital evidence based on blockchain technologies_
Otabek Pirmatov
So, you can submit the certificate to the court. However, the question is how judges
evaluate the evidence. Let's to through an example relevant for e.g. the German or
Japanese system: in these systems, it is up to the discretion of the judge to decide
whether the certificate will be taken into consideration. If the judge believes the
authenticity of the certificate, it will become the basis of the judgment.
Let's suppose that the claim of a defendant in a dispute could be validated with the data
certified with a blockchain transaction. The judge decides on the authenticity of the
submitted evidence based on the opinions of both parties. The defendant will explain the
concept of blockchain immutability achieved with the consensus mechanism, and the
other party will argue the possibility that the information on the blockchain has been
tampered with. After the judge considers both stories and takes a position regarding the
authenticity of the information, s/he will make a decision accordingly[8].
According to Zihui (Katt) Gu, For the blockchain evidence to be admissible, the
authenticity of the source of the electronic data must first be confirmed, whether through
examination of the original or comprehensive consideration of all the evidence at hand[9].
The admissibility of digital evidence is one of the problems of judicial evaluation of
evidence in civil litigation.
In ensuring the admissibility of electronic evidence in foreign countries, transferring it to
the blockchain software or evaluating the evidence in the blockchain software as
admissible evidence is of great importance.
According to Van Yojun, if blockchain technology can be applied to any digital evidence,
regardless of whether it is a criminal or civil trial, the general expected benefits can be
achieved, including: ensuring the integrity and accuracy of data, preventing the
tampering of data or evidence, increasing the transparency of legal proceedings, Court
proceedings are easy to follow, accelerated and simplified[10].
## 2. Issues of application of blockchain technology in the legislation of
foreign countries
The Federal Government of the United States has not exercised its constitutional power
to implement legislation regulating the admissibility of blockchain evidence in court.
Thus, states enjoy residual power to implement their own legislation. The Federal Rules
of Evidence establish a minimum requirement in what is referred to as the ‘best evidence
rule which establishes that the best evidence must be used at trial. Rule 1002 of the
Federal Rules of Evidence states “An original writing, recording, or photograph is required
in order to prove its content unless these rules or a federal statute provides otherwise”.
Several states have regulated blockchain through introducing their own legislation and
rules, particularly with regard to the regulation of cryptocurrency – or as termed by
various legislators, virtual currencies. New York kickstarted legislative developments in
8 [https://www.bernstein.io/blog/2020/1/17/can-digital-data-stored-on-blockchain-be-a-valid-evidence-in-](https://www.bernstein.io/blog/2020/1/17/can-digital-data-stored-on-blockchain-be-a-valid-evidence-in-ip-litigation)
[ip-litigation](https://www.bernstein.io/blog/2020/1/17/can-digital-data-stored-on-blockchain-be-a-valid-evidence-in-ip-litigation)
9 [http://illinoisjltp.com/timelytech/blockchain-based-evidence-preservation-opportunities-and-concerns/](http://illinoisjltp.com/timelytech/blockchain-based-evidence-preservation-opportunities-and-concerns/)
10
[https://www.ithome.com.tw/news/130752](https://www.ithome.com.tw/news/130752)
-----
JANUS.NET, e journal of International Relations
e-ISSN: 1647-7251
Vol. 14, Nº. 1 (May-October 2023), pp. 279-288
_Notes and Reflections_
_Problems of evaluation of digital evidence based on blockchain technologies_
Otabek Pirmatov
the USA through the regulation of virtual currency companie, and eventually several
states followed suit, with 32 states implementing their own rules and regulations. The
states of Illinois, Vermont, Virginia, Washington, Arizona, New York and Ohio have
passed or introduced legislation which specifically regulates the admissibility of
blockchain evidence in court[11].
In April 2018, 1 22 member states signed the Declaration for a European Blockchain
Partnership (EBP) in order to “cooperate on the development of a European Blockchain
Services Infrastructure.”2 With its ambitious goal of identifying initial use cases and
developing functional specifications by the end of the year, the EBP should be an
important catalyst for the use of blockchain technology by European government
agencies[12].
In October 2018, discussions were underway among the Azerbaijani Internet Forum (AIF)
for the Ministry of Justice to implement blockchain technology in several departments
within its remit. Currently, the Ministry provides more than 30 electronic services and 15
information systems and registries, including “electronic notary, electronic courts,
penitentiary service, information systems of non-governmental organizations”, and the
register of the population, among others. Part of the AIF’s plans is to introduce a “mobile
notary office” which would involve the notarization of electronic documents. Through this
process, the registry’s entries will be stored on blockchain which parties will be able to
access but not change, thus preventing falsification. Future plans also include employing
smart contracts in public utility services such as water, gas and electricity[13].
Blockchain technology is a new way to build a network. Today, almost all service systems
in the Internet system work on the basis of a centralized network, that is, the data
warehouse is located on a central server, and users receive data by connecting to this
server. The main difference of blockchain technology is that there is no need for a central
server and all network participants have equal rights. The network database is kept by
each user.
One of the main reasons why evidence based on blockchain technology is considered
admissible by courts is that blockchain technology is transparent, that is, it is not affected
by the human factor.
According to the Decision of the President of the Republic of Uzbekistan dated July 3,
2018, "On measures to develop the digital economy in the Republic of Uzbekistan":
− basic concepts in the field of "blockchain" technologies and principles of its operation;
− powers of state bodies, as well as process participants in the field of "blockchain"
technologies;
− measures of responsibility for using "blockchain" technologies for illegal purposes.
The State Services Agency of the Republic of Uzbekistan has decided that starting from
December 2020, the country's registry offices will operate based on blockchain
technology. However, as of today, this system has not yet been launched. It would be
11 [https://blog.bcas.io/blockchain_court_evidence](https://blog.bcas.io/blockchain_court_evidence)
12 [https://www.eublockchainforum.eu/reports](https://www.eublockchainforum.eu/reports)
13 [https://blog.bcas.io/blockchain_court_evidence](https://blog.bcas.io/blockchain_court_evidence)
-----
JANUS.NET, e journal of International Relations
e-ISSN: 1647-7251
Vol. 14, Nº. 1 (May-October 2023), pp. 279-288
_Notes and Reflections_
_Problems of evaluation of digital evidence based on blockchain technologies_
Otabek Pirmatov
appropriate if the documents issued not only by registry authorities, but also by tax
authorities, cadastral departments, transactions concluded by notary offices, and most
importantly, decisions of district and city mayors and reports issued by electronic auction,
e-active, would be accepted based on blockchain technology.
Agreements concluded by notary offices in civil courts, decisions of district and city
mayors, and reports issued by electronic auction serve as the main written evidence
confirming ownership rights.
Due to the widespread involvement of information technologies in all spheres of social
life in our country, the above bodies are also moving to receive documents in electronic
form.
Also, distribution of electricity based on blockchain technology is being carried out in
Uzbekistan based on South Korean technology. Perhaps, in the future, electricity
contracts in our country may be concluded on the basis of blockchain technology.
## 3. Discussion
With the development of the Internet and information technology, digital data has
gradually become an important part of the evidence system in civil court cases, which
cannot be ignored. Among all types of digital data, blockchain evidence is a relatively
new type.
A proper blockchain is not a proof itself, but a technical implementation method of
storing, transporting and correcting digital data.
Blockchain is just a storage technology, the purpose of which is to ensure the authenticity
and reliability of digital data. The most important thing is to determine the authenticity
of the digital data.
Improvements in blockchain technology can make electronic documents flow more
quickly and improve the efficiency of their assessment in courts. However, compared to
the traditional notarization method of securing electronic evidence, blockchain-based
evidence storage lags behind. That is, there are not enough normative legal documents
on the implementation of blockchain technologies in the field of justice. Notarization,
which has become a means of preventing falsification of electronic documents, is rarely
used in legal practice, because notarization of electronic evidence requires excessive time
and money for the parties.
It includes digital signatures, reliable time stamps and hash value verification to prove
the authenticity of the submitted data using blockchain technology. Parties must be able
to demonstrate how blockchain technology has been used to collect and store evidence.
Due to the decentralization of information in the blockchain network, it is very difficult
for hackers to exploit. Additionally, since each block contains the hash of the previous
block, any transaction within the blockchain is done by changing it.
Check Hash Value: After computing any electronic file using hash algorithm, only one
hash value can be obtained. If the content of the electronic file changes, the resulting
hash value will also change. The uniqueness and non-repeatability of the hash value
ensures the immutability of electronic files.
-----
JANUS.NET, e journal of International Relations
e-ISSN: 1647-7251
Vol. 14, Nº. 1 (May-October 2023), pp. 279-288
_Notes and Reflections_
_Problems of evaluation of digital evidence based on blockchain technologies_
Otabek Pirmatov
The verifier can use the hash value written to the blockchain to verify the original data
to verify that the data is valid and has not been tampered with.
Encrypting evidence can also ensure its safe storage. At a basic level, encryption uses a
secret key to ensure that only those with access can read the file by encrypting the file's
contents.
It is possible to prepare documents based on blockchain technology in applications such
as SharpShark, SynPat, WordProof, Waves, EUCD, DMCA.
The main reason why evidence based on blockchain technology is considered acceptable
evidence in foreign countries is its technological structure. We can see the following
unique features of it:
- at the discretion of one of the parties, it is not possible to change and add (falsify
and destroy) documents based on blockchain technology;
- documents based on blockchain technology are a technology resistant to hacker
attacks, which means that electronic evidence based on blockchain technology
cannot be tampered with by third parties;
- in blockchain technology, there is no need for a central server, and all network
participants have equal rights. A network database stores every user in it.
The lack of possibility of falsification and alteration of the evidence based on blockchain
technology makes it considered acceptable evidence by the courts.
According to the civil procedural law, the admissibility of the evidence must be confirmed
by certain means of proof according to this law.
In order to ensure the admissibility of electronic evidence, it is appropriate to create
electronic documents, electronic transactions using blockchain technology, and to
improve the legislation in this regard.
The following features of blockchain evidence should be considered:
1. To review the authenticity of the blockchain evidence. Specifically, it means that the
court should examine whether the blockchain evidence is likely to be tampered with
in the process of formation, transmission, extraction and display, and to the extent
of such possibility.
2. To review the legitimacy of the blockchain evidence. Specifically, it means that the
court should examine whether the collection, storage and extraction methods of
blockchain evidence comply with the law, and whether they infringe on the legitimate
rights and interests of others.
3. To review the relevance of blockchain evidence. Specifically, it means that the court
should examine whether there is a substantial connection between the blockchain
evidence and the facts to be proved[14].
14 [https://www.chinajusticeobserver.com/a/when-blockchain-meets-electronic-evidence-in-china-s-internet-](https://www.chinajusticeobserver.com/a/when-blockchain-meets-electronic-evidence-in-china-s-internet-courts)
[courts](https://www.chinajusticeobserver.com/a/when-blockchain-meets-electronic-evidence-in-china-s-internet-courts)
-----
JANUS.NET, e journal of International Relations
e-ISSN: 1647-7251
Vol. 14, Nº. 1 (May-October 2023), pp. 279-288
_Notes and Reflections_
_Problems of evaluation of digital evidence based on blockchain technologies_
Otabek Pirmatov
## Conclusion
Blockchain storage solves the problem of securely storing digital data. In a sense,
blockchain storage is an authentication or auxiliary storage method. Currently,
blockchain storage is a more indirect authentication method.
One of the peculiarities of blockchain technology in legal science is that the use of this
technology when concluding transactions or obtaining any official documents from
government authorities greatly simplifies the process of proof. Due to this, the blockchain
allows to track the entire history of changes made to the data stored in the "data" and
reliably protects against illegal attempts to tamper with or falsify the data. Such evidence
would be nearly impossible to challenge, but the risk of hacking or fraudulent activity
remains, albeit partially. Second, if court hearings are held online, the possibility of
blockchain use by court hearing participants will increase even more. Thus, due to the
use of blockchain, it is possible to significantly reduce the time of consideration of cases
in civil courts and to increase the transparency of judicial processes and ensure the
necessary confidentiality of information.
Because public offering of goods and services on social networks has become popular in
our country. Purchase of goods and services on social networks is carried out through
mutual correspondence. Correspondence in the social network can be deleted or
changed. This creates problems in evaluating social network correspondence as evidence
in civil courts.
The adoption of blockchain technologies by social networks may also lead to the use of
social media correspondence as evidence in courts in the future.
## References
Blockchain 24, consulted online, available at [https://blockchain24.pro/blokcheyn-i-](https://blockchain24.pro/blokcheyn-i-yurisprudentsiya)
[yurisprudentsiya](https://blockchain24.pro/blokcheyn-i-yurisprudentsiya)
Chan, Viviene (2020). Blockchain Evidence in Internet Courts in China: The Fast Track
for Evidence Collection for Online Disputes. Consulted online, available at
[https://www.lexology.com/library/detail.aspx?g=1631e87b-155a-40b4-a6aa-](https://www.lexology.com/library/detail.aspx?g=1631e87b-155a-40b4-a6aa-5260a2e4b9bb)
[5260a2e4b9bb](https://www.lexology.com/library/detail.aspx?g=1631e87b-155a-40b4-a6aa-5260a2e4b9bb)
De Filippi, Primavera and Wright, Aaron (2018). _Blockchain and the Law: The Rule of_
_Code. Harvard University Press._
Du, Guodong and Yu, Meng (2021). “When Blockchain Meets Electronic Evidence in
China's Internet Courts”, China Justice Observer Consulted online, available at
[https://www.chinajusticeobserver.com/a/when-blockchain-meets-electronic-evidence-](https://www.chinajusticeobserver.com/a/when-blockchain-meets-electronic-evidence-in-china-s-internet-courts)
[in-china-s-internet-courts](https://www.chinajusticeobserver.com/a/when-blockchain-meets-electronic-evidence-in-china-s-internet-courts)
European Union blockchain observatory & forum, blockchain for government and public
[services (Dec. 7, 2018), https://www.eublockchainforum.eu/reports](https://www.eublockchainforum.eu/reports)
-----
JANUS.NET, e journal of International Relations
e-ISSN: 1647-7251
Vol. 14, Nº. 1 (May-October 2023), pp. 279-288
_Notes and Reflections_
_Problems of evaluation of digital evidence based on blockchain technologies_
Otabek Pirmatov
Fedorov, Pavel (2022). “What is blockchain: everything you need to know about the
technology”, Forbes, consulted online, available at
[https://www.forbes.ru/mneniya/456381-cto-takoe-blokcejn-vse-cto-nuzno-znat-o-](https://www.forbes.ru/mneniya/456381-cto-takoe-blokcejn-vse-cto-nuzno-znat-o-tehnologii)
[tehnologii](https://www.forbes.ru/mneniya/456381-cto-takoe-blokcejn-vse-cto-nuzno-znat-o-tehnologii)
Gazeta.uz (2022). Blockchain technology is not a problem, but it is a problem that has
_to_ _be_ _solved._ Consulted online, available at
[https://www.gazeta.uz/uz/2022/08/26/blockchain-technology/](https://www.gazeta.uz/uz/2022/08/26/blockchain-technology/)
# Gross, Jonas (2020). Legal aspects of blockchain technology. Consulted online, availabe at
[www.jonasgross.medium.com/legal-aspects-of-blockchain-technology-part-1-](http://www.jonasgross.medium.com/legal-aspects-of-blockchain-technology-part-1-blockchain-as-evidence-in-court-704ab7255cf5)
[blockchain-as-evidence-in-court-704ab7255cf5](http://www.jonasgross.medium.com/legal-aspects-of-blockchain-technology-part-1-blockchain-as-evidence-in-court-704ab7255cf5)
Gulyamov, S. (2019). Blockchain technologies in the digital economy. Textbook, p. 114.
iThome (2022). Taiwan Takes the Lead in Judicial Blockchain Applications] An Inventory
_of_ _Global_ _Judicial_ _Blockchain_ _Applications,_ consulted online, available at
[https://www.ithome.com.tw/news/130752](https://www.ithome.com.tw/news/130752)
Michalko, Matej (2019). “Blockchain ‘witness’: a new evidence model in consumer
disputes”. International journal on consumer law and practice. V.7., p.7.
Murray, Andrew (2016). Information Technology Law, p. 517-519.
Okakita, Yuhei (2020). _Can digital data stored on Blockchain be valid evidence in IP_
_litigation?. Consulted online, available at_ [https://www.bernstein.io/blog/2020/1/17/can-](https://www.bernstein.io/blog/2020/1/17/can-digital-data-stored-on-blockchain-be-a-valid-evidence-in-ip-litigation)
[digital-data-stored-on-blockchain-be-a-valid-evidence-in-ip-litigation](https://www.bernstein.io/blog/2020/1/17/can-digital-data-stored-on-blockchain-be-a-valid-evidence-in-ip-litigation)
Pollacco, Alexia (2020). _The Interaction between Blockchain Evidence and Courts – A_
_cross-jurisdictional_ _analysis._ _Consulted_ _online,_ _available_ _at_
[https://blog.bcas.io/blockchain_court_evidence](https://blog.bcas.io/blockchain_court_evidence)
_The Illinois Journal of Law, Technology & Policy, consulted online, available at_
[http://illinoisjltp.com/timelytech/blockchain-based-evidence-preservation-](http://illinoisjltp.com/timelytech/blockchain-based-evidence-preservation-opportunities-and-concerns/)
[opportunities-and-concerns/](http://illinoisjltp.com/timelytech/blockchain-based-evidence-preservation-opportunities-and-concerns/)
**How to cite this note**
Pirmatov, Otabek (2023). Problems of evaluation of digital evidence based on blockchain
technologies. Notes and Reflections in Janus.net, e-journal of international relations. Vol. 14, Nº
1, May-October 2023. Consulted [online] on date of last visit, [https://doi.org/10.26619/1647-](https://doi.org/10.26619/1647-7251.14.1.01)
[7251.14.1.01](https://doi.org/10.26619/1647-7251.14.1.01)
-----
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"license": "CCBY",
"status": "GOLD",
"url": "https://janusnet-ojs.autonoma.pt/index.php/janus/article/download/27/107"
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Plastic waste recycling: existing Indian scenario and future opportunities
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000523657fe1a5879d72c099f619ea0de4424bff
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An Attribute-Based Access Control for IoT Using Blockchain and Smart Contracts
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0010110e322b5ed622e9a57ff2aed1b092b3cf9e
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End of preview. Expand
in Data Studio
DLT-Scientific-Literature
Dataset Description
Dataset Summary
DLT-Scientific-Literature is a specialized corpus of academic publications focused on Distributed Ledger Technology (DLT). This dataset is part of the larger DLT-Corpus collection, designed to support NLP research, language model development, and innovation studies in the DLT domain.
The dataset contains 37,440 scientific documents with 564 million tokens, spanning publications from 1978 to 2025. All documents are in English and have been filtered for domain relevance using a fine-tuned BERT model.
This dataset is part of the DLT-Corpus collection. For the complete corpus including patents and social media data, see: https://huggingface.co/collections/ExponentialScience/dlt-corpus-68e44e40d4e7a3bd7a224402
Languages
English (en)
Dataset Structure
Data Fields
The dataset includes the following fields for each document:
- paperId: Unique identifier from Semantic Scholar
- title: Title of the scientific publication
- authors: List of authors
- year: Publication year
- publicationDate: Full publication date
- venue: Publication venue (journal, conference, etc.)
- publicationVenue: Detailed venue information
- publicationTypes: Type of publication (e.g., JournalArticle, Conference)
- abstract: Abstract of the publication
- text: Full text content in Markdown format
- url: URL to the source document
- openAccessPdf: Link to open access PDF if available
- isOpenAccess: Boolean indicating open access status
- fieldsOfStudy: Academic fields associated with the paper
- s2FieldsOfStudy: Semantic Scholar's field classifications
- references: List of referenced papers
- lang: Language code
- lang_conf: Confidence score for language detection
- tok_len: Token length of the document
- total_tokens: Total number of tokens
Data Splits
This is a single corpus without predefined splits. Users should create their own train/validation/test splits based on their specific research needs.
Dataset Creation
Curation Rationale
DLT-Scientific-Literature was created to address the lack of large-scale, domain-specific text corpora for NLP and computational research in the Distributed Ledger Technology field. The dataset enables researchers to:
- Develop DLT-specific language models and embeddings
- Conduct innovation studies and trend analysis
- Perform text mining on cutting-edge DLT research
- Study the evolution of concepts and terminology in the field
Source Data
Data Collection
Scientific literature was collected from the Semantic Scholar API using domain-specific queries related to blockchain, distributed ledgers, cryptocurrencies, smart contracts, and related technologies.
Data Processing
The collection process involved:
- Query-based retrieval: Using targeted keywords to retrieve relevant publications
- PDF parsing: Converting PDF documents to Markdown format
- Language detection: Filtering for English-language documents
- Length filtering: Removing documents that are too short or too long
- Domain relevance filtering: Using a fine-tuned BERT model to ensure documents are relevant to DLT
Personal and Sensitive Information
This dataset contains only publicly available scientific literature. No personal or confidential data is included. Author names and affiliations are retained as they appear in the original publications, as this is standard academic practice.
Considerations for Using the Data
Discussion of Biases
Potential biases include:
- Geographic bias: Publications may be skewed toward institutions in certain countries
- Language bias: Only English-language publications are included
- Temporal bias: More recent years may have disproportionately more publications
- Venue bias: Certain journals or conferences may be over-represented
- Citation bias: Highly-cited papers may be more likely to be included
Other Known Limitations
- Temporal coverage: While the dataset spans 1978-2025, the distribution is uneven with more recent years heavily represented
- Access limitations: Some publications may be missing due to access restrictions or API limitations
- Quality variation: Academic writing quality and rigor vary across publications
- Parsing errors: PDF-to-Markdown conversion may introduce formatting issues in some documents
Additional Information
Dataset Curators
Walter Hernandez Cruz, Peter Devine, Nikhil Vadgama, Paolo Tasca, Jiahua Xu
Licensing Information
Mixed open-access licenses including:
- Creative Commons Attribution (CC-BY)
- Creative Commons Attribution-ShareAlike (CC-BY-SA)
- Creative Commons Zero (CC0)
- Other permissive open-access licenses
Individual license information is included in the metadata for each document where available. Users should check the specific license for each document before use.
Citation Information
@article{hernandez2025dlt-corpus,
title={DLT-Corpus: A Large-Scale Text Collection for the Distributed Ledger Technology Domain},
author={Hernandez Cruz, Walter and Devine, Peter and Vadgama, Nikhil and Tasca, Paolo and Xu, Jiahua},
year={2025}
}
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Size of downloaded dataset files:
1.25 GB
Size of the auto-converted Parquet files:
1.25 GB
Number of rows:
37,440
Models trained or fine-tuned on ExponentialScience/DLT-Scientific-Literature