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Financial Cryptography and Data Security

Overview of attention for book
Cover of 'Financial Cryptography and Data Security'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Simple Encrypted Arithmetic Library - SEAL v2.1
  3. Altmetric Badge
    Chapter 2 Towards Privacy-Preserving Multi-party Bartering
  4. Altmetric Badge
    Chapter 3 Multi-level Access in Searchable Symmetric Encryption
  5. Altmetric Badge
    Chapter 4 Privacy-Preserving Computations of Predictive Medical Models with Minimax Approximation and Non-Adjacent Form
  6. Altmetric Badge
    Chapter 5 Private Outsourced Kriging Interpolation
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    Chapter 6 An Analysis of FV Parameters Impact Towards Its Hardware Acceleration
  8. Altmetric Badge
    Chapter 7 Controlled Homomorphic Encryption: Definition and Construction
  9. Altmetric Badge
    Chapter 8 ValueShuffle: Mixing Confidential Transactions for Comprehensive Transaction Privacy in Bitcoin
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    Chapter 9 Could Network Information Facilitate Address Clustering in Bitcoin?
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    Chapter 10 Switch Commitments: A Safety Switch for Confidential Transactions
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    Chapter 11 (Short Paper) PieceWork: Generalized Outsourcing Control for Proofs of Work
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    Chapter 12 Enhancing Bitcoin Transactions with Covenants
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    Chapter 13 Decentralized Prediction Market Without Arbiters
  15. Altmetric Badge
    Chapter 14 An Analysis of Bitcoin OP_RETURN Metadata
  16. Altmetric Badge
    Chapter 15 Constant-Deposit Multiparty Lotteries on Bitcoin
  17. Altmetric Badge
    Chapter 16 Exchange Pattern Mining in the Bitcoin Transaction Directed Hypergraph
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    Chapter 17 Incentivizing Blockchain Forks via Whale Transactions
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    Chapter 18 Mixing Coins of Different Quality: A Game-Theoretic Approach
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    Chapter 19 Smart Contracts Make Bitcoin Mining Pools Vulnerable
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    Chapter 20 BatchVote: Voting Rules Designed for Auditability
  22. Altmetric Badge
    Chapter 21 Existential Assertions for Voting Protocols
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    Chapter 22 Marked Mix-Nets
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    Chapter 23 Pseudo-Code Algorithms for Verifiable Re-encryption Mix-Nets
  25. Altmetric Badge
    Chapter 24 Using Selene to Verify Your Vote in JCJ
  26. Altmetric Badge
    Chapter 25 A Roadmap to Fully Homomorphic Elections: Stronger Security, Better Verifiability
  27. Altmetric Badge
    Chapter 26 Enabling Vote Delegation for Boardroom Voting
  28. Altmetric Badge
    Chapter 27 Practical Governmental Voting with Unconditional Integrity and Privacy
  29. Altmetric Badge
    Chapter 28 Findel: Secure Derivative Contracts for Ethereum
  30. Altmetric Badge
    Chapter 29 Decentralized Execution of Smart Contracts: Agent Model Perspective and Its Implications
  31. Altmetric Badge
    Chapter 30 A Concurrent Perspective on Smart Contracts
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    Chapter 31 An Empirical Analysis of Smart Contracts: Platforms, Applications, and Design Patterns
  33. Altmetric Badge
    Chapter 32 Trust in Smart Contracts is a Process, As Well
  34. Altmetric Badge
    Chapter 33 Defining the Ethereum Virtual Machine for Interactive Theorem Provers
  35. Altmetric Badge
    Chapter 34 SmartCast: An Incentive Compatible Consensus Protocol Using Smart Contracts
  36. Altmetric Badge
    Chapter 35 On the Feasibility of Decentralized Derivatives Markets
  37. Altmetric Badge
    Chapter 36 A Proof-of-Stake Protocol for Consensus on Bitcoin Subchains
  38. Altmetric Badge
    Chapter 37 X-Platform Phishing: Abusing Trust for Targeted Attacks Short Paper
  39. Altmetric Badge
    Chapter 38 What to Phish in a Subject?
  40. Altmetric Badge
    Chapter 39 Unpacking Spear Phishing Susceptibility
Overall attention for this book and its chapters
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (96th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Mentioned by

1 blog
1 policy source
89 tweeters
4 patents


4 Dimensions

Readers on

72 Mendeley
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Financial Cryptography and Data Security
Published by
arXiv, January 2017
DOI 10.1007/978-3-319-70278-0
978-3-31-970277-3, 978-3-31-970278-0

Massimo Bartoletti, Livio Pompianu


Michael Brenner, Kurt Rohloff, Joseph Bonneau, Andrew Miller, Peter Y.A. Ryan, Vanessa Teague, Andrea Bracciali, Massimiliano Sala, Federico Pintore, Markus Jakobsson

Twitter Demographics

The data shown below were collected from the profiles of 89 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 72 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Japan 1 1%
Luxembourg 1 1%
Unknown 70 97%

Demographic breakdown

Readers by professional status Count As %
Student > Master 93 129%
Student > Ph. D. Student 65 90%
Researcher 39 54%
Student > Bachelor 39 54%
Student > Doctoral Student 21 29%
Other 46 64%
Readers by discipline Count As %
Computer Science 172 239%
Business, Management and Accounting 35 49%
Engineering 31 43%
Economics, Econometrics and Finance 19 26%
Social Sciences 17 24%
Other 15 21%

Attention Score in Context

This research output has an Altmetric Attention Score of 91. 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 18 August 2020.
All research outputs
of 16,282,554 outputs
Outputs from arXiv
of 646,925 outputs
Outputs of similar age
of 268,446 outputs
Outputs of similar age from arXiv
of 18,121 outputs
Altmetric has tracked 16,282,554 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 646,925 research outputs from this source. They receive a mean Attention Score of 3.8. This one has done particularly well, scoring higher than 99% of its peers.
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 268,446 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 96% of its contemporaries.
We're also able to compare this research output to 18,121 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 99% of its contemporaries.