一种基于隐私保护下的多方记录链接方法
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国家自然科学基金(61472070,61672142);国家重点基础研究发展计划(973)(2012CB316201)


Multi-Party Privacy-Preserving Record Linkage Approach
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National Natural Science Foundation of China (61472070, 61672142); National Grand Fundamental Research Program of China (973) (2012CB316201)

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    摘要:

    多方隐私保护下的记录链接(privacy-preserving record linkage,简称PPRL)是在隐私保护下,从多个数据源中找出代表现实世界中同一实体的过程.该过程除了最终匹配结果被数据源之间共享外,其他信息均未被泄露.随着数据量的日益增大和现实世界数据质量问题的存在(如拼写错误、顺序颠倒等),多方PPRL方法的可扩展性和容错性面临挑战.目前,已有的大部分多方PPRL方法都是精确匹配方法,不具有容错性.还有少部分多方PPRL近似方法具有容错性,但在处理存在质量问题的数据时,由于容错性差和时间代价过大,并不能有效地找出数据源间的共同实体.因此,提出一种结合布隆过滤、安全合计、动态阈值、检查机制和改进的Dice相似度函数的多方PPRL近似方法.首先,利用布隆过滤将各数据源中的每条记录信息转换成由0和1组成的位数组.然后,计算每个对应位置bit 1所占的比率,并利用动态阈值和检查机制来判定匹配成功的位置.最后,通过改进的Dice相似度函数计算出记录间的相似度,进而判断记录间是否匹配成功.实验结果表明:所提出的方法具有较好的可扩展性,并且在保证查准率的同时,比已有的多方近似PPRL方法具有更高的容错性.

    Abstract:

    Multi-party privacy-preserving record linkage is the process of identifying records that correspond to the same real-world entities across several databases without revealing any sensitive information about these entities. With the increasing amount of data and the real-world data quality issues (such as spelling errors and wrong order), scalability and fault tolerance of PPRL have become the main challenges. At present, most of the existing multi-party PPRL methods apply exact match without fault-tolerant. There are a few other PPRL approximate methods with fault-tolerant, but when dealing with the existing data quality issues, due to the low fault-tolerance and high time cost, they cannot effectively find out the common entities between databases. To tackle this issue, this paper proposes a multi-party PPRL approximate approach combined with bloom filter, secure summation, dynamic threshold, check mechanism, and improved Dice similarity function. First, bloom filter is used to convert each record in the databases to an array of 1 and 0. Then, ratio of bit 1 is calculated for each corresponding position, and dynamic threshold and check mechanism are used to determine matched position.Finally, the similarity between records is calculated by improved Dice similarity function to judge whether records are matched. Experimental results show the proposed method has good scalability and higher fault tolerance than the existing multi-party PPRL approximate method with good precision.

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韩姝敏,申德荣,聂铁铮,寇月,于戈.一种基于隐私保护下的多方记录链接方法.软件学报,2017,28(9):2281-2292

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  • 收稿日期:2016-07-11
  • 最后修改日期:2016-11-10
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  • 在线发布日期: 2017-09-02
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