8,367 research outputs found
Using quantum key distribution for cryptographic purposes: a survey
The appealing feature of quantum key distribution (QKD), from a cryptographic
viewpoint, is the ability to prove the information-theoretic security (ITS) of
the established keys. As a key establishment primitive, QKD however does not
provide a standalone security service in its own: the secret keys established
by QKD are in general then used by a subsequent cryptographic applications for
which the requirements, the context of use and the security properties can
vary. It is therefore important, in the perspective of integrating QKD in
security infrastructures, to analyze how QKD can be combined with other
cryptographic primitives. The purpose of this survey article, which is mostly
centered on European research results, is to contribute to such an analysis. We
first review and compare the properties of the existing key establishment
techniques, QKD being one of them. We then study more specifically two generic
scenarios related to the practical use of QKD in cryptographic infrastructures:
1) using QKD as a key renewal technique for a symmetric cipher over a
point-to-point link; 2) using QKD in a network containing many users with the
objective of offering any-to-any key establishment service. We discuss the
constraints as well as the potential interest of using QKD in these contexts.
We finally give an overview of challenges relative to the development of QKD
technology that also constitute potential avenues for cryptographic research.Comment: Revised version of the SECOQC White Paper. Published in the special
issue on QKD of TCS, Theoretical Computer Science (2014), pp. 62-8
Practical cryptographic strategies in the post-quantum era
We review new frontiers in information security technologies in
communications and distributed storage technologies with the use of classical,
quantum, hybrid classical-quantum, and post-quantum cryptography. We analyze
the current state-of-the-art, critical characteristics, development trends, and
limitations of these techniques for application in enterprise information
protection systems. An approach concerning the selection of practical
encryption technologies for enterprises with branched communication networks is
introduced.Comment: 5 pages, 2 figures; review pape
Deep Active Learning for Named Entity Recognition
Deep learning has yielded state-of-the-art performance on many natural
language processing tasks including named entity recognition (NER). However,
this typically requires large amounts of labeled data. In this work, we
demonstrate that the amount of labeled training data can be drastically reduced
when deep learning is combined with active learning. While active learning is
sample-efficient, it can be computationally expensive since it requires
iterative retraining. To speed this up, we introduce a lightweight architecture
for NER, viz., the CNN-CNN-LSTM model consisting of convolutional character and
word encoders and a long short term memory (LSTM) tag decoder. The model
achieves nearly state-of-the-art performance on standard datasets for the task
while being computationally much more efficient than best performing models. We
carry out incremental active learning, during the training process, and are
able to nearly match state-of-the-art performance with just 25\% of the
original training data
Classical Homomorphic Encryption for Quantum Circuits
We present the first leveled fully homomorphic encryption scheme for quantum
circuits with classical keys. The scheme allows a classical client to blindly
delegate a quantum computation to a quantum server: an honest server is able to
run the computation while a malicious server is unable to learn any information
about the computation. We show that it is possible to construct such a scheme
directly from a quantum secure classical homomorphic encryption scheme with
certain properties. Finally, we show that a classical homomorphic encryption
scheme with the required properties can be constructed from the learning with
errors problem
A quantum key distribution protocol for rapid denial of service detection
We introduce a quantum key distribution protocol designed to expose fake
users that connect to Alice or Bob for the purpose of monopolising the link and
denying service. It inherently resists attempts to exhaust Alice and Bob's
initial shared secret, and is 100% efficient, regardless of the number of
qubits exchanged above the finite key limit. Additionally, secure key can be
generated from two-photon pulses, without having to make any extra
modifications. This is made possible by relaxing the security of BB84 to that
of the quantum-safe block cipher used for day-to-day encryption, meaning the
overall security remains unaffected for useful real-world cryptosystems such as
AES-GCM being keyed with quantum devices.Comment: 13 pages, 3 figures. v2: Shifted focus of paper towards DoS and added
protocol 4. v1: Accepted to QCrypt 201
Preventing False Discovery in Interactive Data Analysis is Hard
We show that, under a standard hardness assumption, there is no
computationally efficient algorithm that given samples from an unknown
distribution can give valid answers to adaptively chosen
statistical queries. A statistical query asks for the expectation of a
predicate over the underlying distribution, and an answer to a statistical
query is valid if it is "close" to the correct expectation over the
distribution.
Our result stands in stark contrast to the well known fact that exponentially
many statistical queries can be answered validly and efficiently if the queries
are chosen non-adaptively (no query may depend on the answers to previous
queries). Moreover, a recent work by Dwork et al. shows how to accurately
answer exponentially many adaptively chosen statistical queries via a
computationally inefficient algorithm; and how to answer a quadratic number of
adaptive queries via a computationally efficient algorithm. The latter result
implies that our result is tight up to a linear factor in
Conceptually, our result demonstrates that achieving statistical validity
alone can be a source of computational intractability in adaptive settings. For
example, in the modern large collaborative research environment, data analysts
typically choose a particular approach based on previous findings. False
discovery occurs if a research finding is supported by the data but not by the
underlying distribution. While the study of preventing false discovery in
Statistics is decades old, to the best of our knowledge our result is the first
to demonstrate a computational barrier. In particular, our result suggests that
the perceived difficulty of preventing false discovery in today's collaborative
research environment may be inherent
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