基于自适应组合过滤器的流数据隐私保护查询策略

PRIVACY PROTECTION QUERY STRATEGY FOR STREAMING DATA BASED ON ADAPTIVE COMBINATION FILTERS

  • 摘要: 为了同时兼顾隐私保护和查询性能,提出一种基于自适应组合过滤器的隐私保护查询策略。引入一种自适应窗口局部敏感哈希过滤器,将该过滤器与布隆过滤器相结合,从而对彼此相似或在相似范围内的值进行模糊匹配。提出一种改进局部差分隐私机制,该机制为具有相似或更低隐私预算的流数据提高了查询效率,减少了实时查询的响应时间。通过真实和合成的英语单词数据集对提出方法进行实验验证,结果证明提出方法能够有效保证流数据查询和隐私保护性能。

     

    Abstract: In order to simultaneously balance privacy protection and query performance, a privacy protection query strategy based on adaptive combination filters is proposed. An adaptive window locally sensitive hash filter was introduced, which combines with Bloom filter to perform fuzzy matching for similar or within-range values. An improved local differential privacy mechanism was proposed to improve query efficiency for stream data with similar or lower privacy budget and reduce real-time query response time. Experiments on real and synthetic English word datasets verify the effectiveness of the proposed method.

     

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