电子学报 ›› 2018, Vol. 46 ›› Issue (5): 1113-1120.DOI: 10.3969/j.issn.0372-2112.2018.05.014

• 学术论文 • 上一篇    下一篇

面向大数据定价的委托拍卖方案

尹鑫, 田有亮, 王海龙   

  1. 1. 贵州大学计算机科学与技术学院, 贵州贵阳 550025;
    2. 贵州省公共大数据重点实验室, 贵州贵阳 550025;
    3. 贵州大学密码学与数据安全研究所, 贵州贵阳 550025
  • 收稿日期:2017-03-27 修回日期:2017-05-15 出版日期:2018-05-25
    • 通讯作者:
    • 田有亮
    • 作者简介:
    • 尹鑫 女,1992年生,山东莱芜人,硕士研究生,主要研究方向为密码学与安全协议.E-mail:csyxcryp@163.com
    • 基金资助:
    • 国家自然科学基金 (No.61363068,No.61662009,No.61772008); 贵州省教育厅科技拔尖人才支持项目 (No.黔教合KY字[2016]060); 贵州大学引进人才科研项目 (No.贵大人基合字 (2015)53号); 贵州大学研究生创新基金 (No.2016050,No.院创201702)

Delegation Auction Scheme for Big Data Pricing

YIN Xin, TIAN You-liang, WANG Hai-long   

  1. 1. College of Computer Science & Technology, Guizhou University, Guiyang, Guizhou 550025, China;
    2. Guizhou Provincial Key Laboratory of Public Big Data, Guiyang, Guizhou 550025, China;
    3. Institute of Cryptography & Data Security, Guizhou University, Guiyang, Guizhou 550025, China
  • Received:2017-03-27 Revised:2017-05-15 Online:2018-05-25 Published:2018-05-25
    • Corresponding author:
    • TIAN You-liang
    • Supported by:
    • National Natural Science Foundation of China (No.61363068, No.61662009, No.61772008); Science and Technology Top-notch Talents Support Program of Education Department of Guizhou Province (No.黔教合KY字[2016]060); Guizhou University Introduction of Talent Research Project (No.贵大人基合字 (2015)53号); Postgraduate Innovation Fund of Guizhou University (No.2016050, No.院创201702)

摘要: 大数据合理定价是当前大数据交易中亟待解决的具有一定挑战性问题之一.本文针对大数据定价困难问题,基于Micali-Rabin的安全计算技术提出一种具有大数据定价功能的安全委托拍卖方案.在方案中首先基于Micali-Rabin的随机向量表示方法设计满足标价密封性的大数据拍卖及验证算法.其次,基于Merkle树和Bit承诺协议实现大数据交易中数据的完整性和底价的不可否认性,特别是在定价阶段,利用一种特殊的多方安全计算协议隐藏大数据的底价,以此保障了大数据交易的公平性.最后,方案安全性和性能分析表明,该方案特别适用于大数据交易场景下的数据委托拍卖.

关键词: 大数据定价, Micali-Rabin随机向量表示, 匿名性, 密封拍卖

Abstract: The reasonable pricing of big data is one of the most challenging problems in big data transaction,which needs to be solved urgently.This paper,based on Micali-Rabin's secure computing technology,presents a secure delegation auction scheme with the function of big data pricing.First,based on Micali-Rabin's random vector representation methods,we design an auction,as well as a verification algorithm with the property of the sealed bid.Second,the big data's integrity and non-repudiation of the reserve price are realized by Merkle tree and Bit commitment protocol respectively,especially in the pricing stage the use of a special multi-party security computing protocol to hide the reserve price of big data,whereby ensuring the fairness of the big data transaction.Finally,as the scheme's security and performance analysis indicate that it is particularly suitable for delegation auction in the context of the big data transaction.

Key words: big data pricing, Micali-Rabin's random vector representation, anonymity, sealed auction

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