参与式感知中隐私保护的差异化数据分享协议

Privacy-preserving various data sharing protocol in participatory sensing

参与式感知中用户不仅对数据匹配度有要求,对数据差异化也同样有要求,为了既能满足用户对数据匹配度和差异化数据的需求,也能保护用户的偏好隐私,提出了一种隐私保护的差异化数据分享协议。该协议首先将交互双方的数据表示为两个整数集合,并且利用计数布隆过滤器(CBF)计算两个集合的集合交,以集合交的结果作为数据类型匹配度;其次利用CBF能删除元素的功能,计算两个集合的差异化数据值;最后将数据类型匹配度和差异化数据值与预先设定的阈值比较,判断是否符合交互条件,同时,对CBF的构造方法进行了改进,用以保护用户的偏好隐私。理论分析和实验结果表明,与基于布隆过滤器(BF)的非加密匹配协议相比,该协议克服了匹配结果偏大的缺陷,同时计算开销减少了50%以上。该协议在保护用户偏好隐私和满足用户对差异化数据需求的同时,具有较高的匹配精度和效率。

In the process of participatory sensing, not only data matching level but also data variation is required by users. In order to meet the aforementioned two requirements, meanwhile, to protect users＇ preference privacy, a privacy- preserving various data sharing protocol was proposed. Firstly, both interactive data were processed to two sets of integer and Counting Bloom Filter （CBF） was utilized to calculate the intersection of the two sets of integer, the result of which was used as data matching level. Secondly, the function to delete elements of CBF was utilized to calculate the value of various data. Lastly, the data matching level and the difference between various data were compared with pre-set threshold, so as to decide whether they complied with interactive condition. In the meantime, the structuring method of CBF was improved to protect users＇ preference privacy. Theoretical analysis and experiment results show the following facts： compared with protocols based on non-cryptographic Bloom Filter （BF）, the problem of relatively large results is overcome and computational overhead is saved by more than 50%. Users＇ preference privacy is protected and the need of various data is met in the proposed protocol. In addition, the proposed protocol enjoys higher matching precision and efficiency.