作　　者： (王涛春）; (崔壮壮）; (刘盈）;

机构地区： 安徽师范大学数学计算机科学学院,安徽芜湖241002 网络与信息安全安徽省重点实验室（安徽师范大学）,安徽芜湖241002

出　　处： 《计算机应用》 2017年第9期2563-2566,2594,共5页

摘　　要： 隐私保护已经成为拓展无线传感器网络(WSN)应用的关键因素,是当前的研究热点。针对传感器网络中感知数据的安全性问题,提出了两层传感器网络中隐私保护的等区间近似查询(PEIAQ)算法。首先,将传感器节点编号及其采集的数据等信息隐藏在随机向量中;然后,基站根据接收到的向量信息构造线性方程组,从而得到包含全局统计信息的直方图;最后,根据直方图完成近似查询。此外,PEIAQ利用数据扰动技术和传感器节点与基站共享密钥的方式来对感知数据进行加密,保证了感知数据的隐私性。仿真实验显示,PEIAQ的通信量在查询阶段明显低于隐私保护通用近似查询(PGAQ)的通信量,约节省60%,因此,该PEIAQ具有低能耗、高效率等特点。 Privacy preservation, a key factor in expanding the application of Wireless Sensor Network （WSN）, is the current research hotspot. In view of the privacy of sensory data in WSN, Privacy-preserving Equal-Interval Approximate Query （PEIAQ） algorithm in two-tiered sensor networks based on data aggregation was proposed. Firstly, sensor node IDs and sensory data were concealed in a random vector, and then linear equations were worked out by the base station based on the random vector. As a result, a histogram containing global statistics was formed, and finally the results of approximate query were obtained. In addition, sensory data were encrypted through perturbation technique and sharing key between the sensor node and base station, which can ensure the privacy of sensory data. Simulation experiments show that the PEIAQ has a 60% decrease approximately in the traffic compared with PGAQ （Privacy-preserving Generic Approximate Query） in the query phase. Therefore, PEIAQ is efficient and costs low-energy.

关 键 词： 两层传感器网络 隐私保护 近似查询 数据聚集