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Post-Quantum Cryptography

Overview of attention for book
Cover of 'Post-Quantum Cryptography'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Using LDGM Codes and Sparse Syndromes to Achieve Digital Signatures
  3. Altmetric Badge
    Chapter 2 Quantum Algorithms for the Subset-Sum Problem
  4. Altmetric Badge
    Chapter 3 Improved Lattice-Based Threshold Ring Signature Scheme
  5. Altmetric Badge
    Chapter 4 Degree of Regularity for HFEv and HFEv-
  6. Altmetric Badge
    Chapter 5 Software Speed Records for Lattice-Based Signatures
  7. Altmetric Badge
    Chapter 6 Solving the Shortest Vector Problem in Lattices Faster Using Quantum Search
  8. Altmetric Badge
    Chapter 7 An Efficient Attack of a McEliece Cryptosystem Variant Based on Convolutional Codes
  9. Altmetric Badge
    Chapter 8 Extended Algorithm for Solving Underdefined Multivariate Quadratic Equations
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    Chapter 9 Quantum Key Distribution in the Classical Authenticated Key Exchange Framework
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    Chapter 10 Cryptanalysis of Hash-Based Tamed Transformation and Minus Signature Scheme
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    Chapter 11 A Classification of Differential Invariants for Multivariate Post-quantum Cryptosystems
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    Chapter 12 Secure and Anonymous Hybrid Encryption from Coding Theory
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    Chapter 13 Fast Verification for Improved Versions of the UOV and Rainbow Signature Schemes
  15. Altmetric Badge
    Chapter 14 The Hardness of Code Equivalence over $\mathbb{F}_q$ and Its Application to Code-Based Cryptography
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    Chapter 15 Timing Attacks against the Syndrome Inversion in Code-Based Cryptosystems
  17. Altmetric Badge
    Chapter 16 Simple Matrix Scheme for Encryption
  18. Altmetric Badge
    Chapter 17 Multivariate Signature Scheme Using Quadratic Forms
Attention for Chapter 6: Solving the Shortest Vector Problem in Lattices Faster Using Quantum Search
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2 X users

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Chapter title
Solving the Shortest Vector Problem in Lattices Faster Using Quantum Search
Chapter number 6
Book title
Post-Quantum Cryptography
Published in
Lecture notes in computer science, January 2013
DOI 10.1007/978-3-642-38616-9_6
Book ISBNs
978-3-64-238615-2, 978-3-64-238616-9
Authors

Thijs Laarhoven, Michele Mosca, Joop van de Pol, Laarhoven, Thijs, Mosca, Michele, van de Pol, Joop

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 30 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Japan 1 3%
Canada 1 3%
Unknown 28 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 30%
Researcher 5 17%
Student > Master 4 13%
Professor > Associate Professor 2 7%
Student > Bachelor 2 7%
Other 4 13%
Unknown 4 13%
Readers by discipline Count As %
Computer Science 16 53%
Mathematics 5 17%
Physics and Astronomy 3 10%
Materials Science 1 3%
Engineering 1 3%
Other 0 0%
Unknown 4 13%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 12 April 2017.
All research outputs
#16,719,822
of 25,376,646 outputs
Outputs from Lecture notes in computer science
#4,632
of 8,151 outputs
Outputs of similar age
#189,976
of 293,970 outputs
Outputs of similar age from Lecture notes in computer science
#184
of 317 outputs
Altmetric has tracked 25,376,646 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,151 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.2. This one is in the 41st percentile – i.e., 41% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 293,970 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 33rd percentile – i.e., 33% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 317 others from the same source and published within six weeks on either side of this one. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.