通信学报 ›› 2021, Vol. 42 ›› Issue (6): 107-117.doi: 10.11959/j.issn.1000-436x.2021122

• 学术论文 • 上一篇    

差分隐私下多重一致性约束问题的逼近方法

蔡剑平1, 刘西蒙1, 熊金波2, 应作斌3, 吴英杰1   

  1. 1 福州大学数学与计算机科学学院,福建 福州 350108
    2 福建师范大学数学与信息学院,福建 福州 350117
    3 新加坡南洋理工大学电气与电子工程学院,新加坡 639798
  • 修回日期:2021-04-03 出版日期:2021-06-01 发布日期:2021-06-01
  • 作者简介:蔡剑平(1990− ),男,福建漳州人,福州大学博士生,主要研究方向为差分隐私、矩阵分析及理论、最优化理论、大数据技术及理论等
    刘西蒙(1988− ),男,陕西西安人,博士,福州大学研究员、福建省“闽江学者”特聘教授,主要研究方向为隐私计算、密文数据挖掘、大数据隐私保护、可搜索加密等
    熊金波(1981− ),男,湖南益阳人,博士,福建师范大学教授,主要研究方向为安全深度学习、移动群智感知、隐私保护技术等
    应作斌(1982− ),男,安徽芜湖人,博士,新加坡南洋理工大学在站博士后,主要研究方向为基于属性的加密、区块链及隐私保护机器学习
    吴英杰(1979− ),男,福建泉州人,博士,福州大学教授、博士生导师,主要研究方向为数据安全隐私保护、工业大数据分析、智能医疗
  • 基金资助:
    国家自然科学基金资助项目(62072109);国家自然科学基金资助项目(U1804263);国家自然科学基金资助项目(61702105);国家自然科学基金资助项目(62002062)

Approximation method of multiple consistency constraint under differential privacy

Jianping CAI1, Ximeng LIU1, Jinbo XIONG2, Zuobin YING3, Yingjie WU1   

  1. 1 College of Mathematics and Computer Science, Fuzhou University, Fuzhou 350108, China
    2 College of Mathematics and Informatics, Fujian Normal University, Fuzhou 350117, China
    3 School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798, Singapore
  • Revised:2021-04-03 Online:2021-06-01 Published:2021-06-01
  • Supported by:
    The National Natural Science Foundation of China(62072109);The National Natural Science Foundation of China(U1804263);The National Natural Science Foundation of China(61702105);The National Natural Science Foundation of China(62002062)

摘要:

为了解决差分隐私下多重一致性约束的最优发布问题,通过分析最优一致性发布原理提出了多重一致性约束问题的逼近方法。所提方法的主要思想是将一致性约束问题划分为多个一致性约束子问题,通过反复独立地求解各一致性约束子问题实现原问题的最优一致性发布。其优势在于一致性约束问题划分之后,子问题往往更容易求解或者实现子问题最优一致性发布的技术已相当成熟,从而能够解决更加复杂的差分隐私最优发布问题。分析论证了逼近方法的收敛性,保证任意一致性约束子问题的划分均能实现原问题的最优一致性发布。并且,以销量直方图发布为例,基于多重一致性约束问题的逼近方法设计了差分隐私餐馆销量直方图一致性并行发布算法。实验表明,该算法相比通用解法可提升效率高达400倍,并且具备处理百万级大规模数据的能力。

关键词: 差分隐私, 一致性约束, 逼近方法, 收敛性, 并行计算

Abstract:

Under differential privacy, to solve the optimal publishing problem with multiple consistency constraints, an approximation method of multiple consistency constraints was proposed by the theoretical analysis of the principle of optimal consistency release.The main idea was to divide the consistency constraint problem into several consistency constraint sub-problems and then achieve the original problem's optimal consistency release by solving each consistency constraint sub-problem repeatedly and independently.The advantage was that after the consistency constraint problem divided, the sub-problems were often easier to solve, or the technology to achieve optimal and consistent release of sub-problems is quite mature.Therefore more complex differential privacy optimal release problem could be solved.After analysis, the approximation method's convergence was fully demonstrated, ensuring that any partition of consistency constrained sub-problems can always achieve the optimal consistency release of the original problem.Furthermore, taking the sales histogram publishing as an example, based on the approximation method of multiple consistency constraints, a parallel algorithm was designed with optimal consistency release under differential privacy.The experimental results show that the algorithm's efficiency is 400 times higher than that of the general solution, and the algorithm can process millions of large-scale data.

Key words: differential privacy, consistency constraint, approximation method, convergence, parallel computing

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