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AABN: Anonymity Assessment Model Based on Bayesian Network With Application to Blockchain

     

摘要

Blockchain is a technology that uses community validation to keep synchro-nized the content of ledgers replicated across multiple users, which is the underlying tech-nology of digital currency like bitcoin. The an-onymity of blockchain has caused widespread concern. In this paper, we put forward AABN, an Anonymity Assessment model based on Bayesian Network. Firstly, we investigate and analyze the anonymity assessment techniques, and focus on typical anonymity assessment schemes. Then the related concepts involved in the assessment model are introduced and the model construction process is described in detail. Finally, the anonymity in the MIX anonymous network is quantitatively evalu-ated using the methods of accurate reasoning and approximate reasoning respectively, and the anonymity assessment experiments under different output strategies of the MIX anony-mous network are analyzed.

著录项

  • 来源
    《中国通信》|2019年第6期|55-68|共14页
  • 作者单位

    School of Software Engineering, Beijing University of Posts and Telecommunications, 100876 Beijing, China;

    Key Laboratory of Trustworthy Distributed Computing and Service (Beijing University of Posts and Telecommunications), Ministry of Education, 100876 Beijing, China;

    School of Software Engineering, Beijing University of Posts and Telecommunications, 100876 Beijing, China;

    Key Laboratory of Trustworthy Distributed Computing and Service (Beijing University of Posts and Telecommunications), Ministry of Education, 100876 Beijing, China;

    Information Security Center, School of Cyberspace Security, Beijing University of Posts and Telecommunications, Beijing 100876, China;

    School of Software Engineering, Beijing University of Posts and Telecommunications, 100876 Beijing, China;

    Key Laboratory of Trustworthy Distributed Computing and Service (Beijing University of Posts and Telecommunications), Ministry of Education, 100876 Beijing, China;

  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

  • 入库时间 2023-07-25 20:36:42

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