论文部分内容阅读
在无线传感网络的研究中,保护隐私数据聚集算法是一个关键问题.设计高效的具有隐私保护功能的数据聚集算法,降低通信带宽,提高网络的寿命和安全性是保护私隐数据聚集研究中的热点问题.国内外现有的保护隐私数据聚集算法,除PEQ(Privacy-preserving Scheme for Exact Query Evaluation)算法外,其它算法大多是根据不同的统计数据类型来设计相应的保护隐私的数据聚集算法,这些算法只能聚集某一种数据,功能单一,应用起来具有一定的局限性.同时,PEQ算法的通信带宽和计算量都比较大.针对上述问题,设计了一种基于数据混淆的数据汇集算法.该算法通过在数据聚集前加入混淆数据,聚集结束后删除混淆数据,来达到保护隐私的目的.与现有的其它方案相比,该方案计算和通信开销较少,并且一次可以聚集多种统计数据.
In the research of wireless sensor network, the protection of privacy data aggregation algorithm is a key issue.Efficient data aggregation algorithm with privacy protection function is designed to reduce the communication bandwidth and improve the life span and security of the network.In the research of privacy data aggregation The existing privacy protection algorithms at home and abroad, except PEQ (Privacy-preserving Scheme for Exact Query Evaluation) algorithm, are based on different types of statistical data to design the appropriate protection of privacy data aggregation algorithm , These algorithms can only aggregate a certain kind of data and have a single function and some limitations in application.At the same time, the communication bandwidth and the computational load of the PEQ algorithm are relatively large.According to the above problems, a data collection based on data obfuscation This algorithm achieves the goal of protecting privacy by adding obfuscated data before data aggregation and deleting obfuscated data after aggregation.Compared with other existing schemes, the proposed algorithm has less computational and communication overhead and can aggregate more Statistics.