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The success of Bitcoin has generated significant interest in the financial community to understand whether the technological underpinnings of the cryptocurrency paradigm can be leveraged to improve the efficiency of financial processes in the existing infrastructure. Various alternative proposals, most

The success of Bitcoin has generated significant interest in the financial community to understand whether the technological underpinnings of the cryptocurrency paradigm can be leveraged to improve the efficiency of financial processes in the existing infrastructure. Various alternative proposals, most notably, Ripple and Ethereum, aim to provide solutions to the financial community in different ways. These proposals derive their security guarantees from either the computational hardness of proof-of-work or voting based distributed consensus mechanism, both of which can be computationally expensive. Furthermore, the financial audit requirements for a participating financial institutions have not been suitably addressed.

This thesis presents a novel approach of constructing a non-consensus based decentralized financial transaction processing model with a built-in efficient audit structure. The problem of decentralized inter-bank payment processing is used for the model design. The two key insights used in this work are (1) to utilize a majority signature based replicated storage protocol for transaction authorization, and (2) to construct individual self-verifiable audit trails for each node as opposed to a common Blockchain. Theoretical analysis shows that the model provides cryptographic security for transaction processing and the presented audit structure facilitates financial auditing of individual nodes in time independent of the number of transactions.
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    Title
    • A non-consensus based decentralized financial transaction processing model with support for efficient auditing
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    Date Created
    2016
    Resource Type
  • Text
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    Note
    • thesis
      Partial requirement for: M.S., Arizona State University, 2016
    • bibliography
      Includes bibliographical references (pages 74-75)
    • Field of study: Computer science

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    by Saurabh Gupta

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