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Trustless Framework for Iterative Double Auction Based on Blockchain

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Security and Privacy in Communication Networks (SecureComm 2019)

Abstract

One of the major problems in current implementations of iterative double auction is that they rely on a trusted third party to handle the auction process. This imposes the risk of single point of failures and monopoly. In this paper, we aim to tackle this problem by proposing a novel decentralized and trustless framework for iterative double auction based on blockchain. Our design adopts the smart contract and state channel technologies to enable a double auction process among parties that do not trust each other, while minimizing the blockchain transactions. We provide a formal development of the framework and highlight the security of our design against adversaries.

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Acknowledgment

This paper is partially supported by DTRA HDTRA1-14-1-0055 and NSF CNS-1814614.

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Authors and Affiliations

  1. Department of Computer and Information Science and Engineering, University of Florida, Gainesville, FL, 32611, USA

    Truc D. T. Nguyen & My T. Thai

Authors
  1. Truc D. T. Nguyen
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  2. My T. Thai
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Corresponding author

Correspondence to Truc D. T. Nguyen .

Editor information

Editors and Affiliations

  1. George Mason University, Fairfax, VA, USA

    Songqing Chen

  2. The University of Texas at San Antonio, San Antonio, TX, USA

    Kim-Kwang Raymond Choo

  3. Boston University, Lowell, MA, USA

    Xinwen Fu

  4. Virginia Tech, Blacksburg, VA, USA

    Wenjing Lou

  5. University of Central Florida, Orlando, FL, USA

    Aziz Mohaisen

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© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Nguyen, T.D.T., Thai, M.T. (2019). Trustless Framework for Iterative Double Auction Based on Blockchain. In: Chen, S., Choo, KK., Fu, X., Lou, W., Mohaisen, A. (eds) Security and Privacy in Communication Networks. SecureComm 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 304. Springer, Cham. https://doi.org/10.1007/978-3-030-37228-6_1

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  • DOI: https://doi.org/10.1007/978-3-030-37228-6_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-37227-9

  • Online ISBN: 978-3-030-37228-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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