两层传感网隐私保护的不完全数据Skyline查询协议

感知节点感知数据易受外界环境影响，使得不完全数据广泛存在于无线传感器网络中，且感知数据面临严重的隐私威胁。针对两层传感器网络不完全数据查询过程中存在的隐私泄露问题，提出一种基于置换和桶技术的两层传感器网络隐私保护的不完全数据Skyline查询协议（PPIS）。为了实现对不完全数据的Skyline查询，PPIS将缺失属性值置换为数据域的上界值，并将不完全数据映射到桶中；为了保证数据隐私性，PPIS首先将桶区间转化为前缀编码，然后将前缀编码加载到Bloom过滤器中，保证存储节点在无需数据和桶区间明文的前提下执行查询处理；为了保证查询结果的完整性，PPIS采用Merkle哈希树构造完整性验证编码，实现对查询结果的完整性验证。理论分析和仿真实验验证了PPIS的安全性和有效性，与现有隐私保护Skyline查询协议SMQ和SSQ相比，PPIS通信能耗节省了70%以上。

Privacy-preserving incomplete data Skyline query protocol in two-tiered sensor networks

The sensor data of sensor node is easy to be influenced by the external environment, which makes the incomplete data exist widely in the wireless sensor network and the sensor data face the serious privacy threat. Aiming at the problem of privacy leakage during the query process of incomplete data in two-tiered sensor networks, a Privacy-Preserving Incomplete data Skyline query protocol in two-tiered sensor network (PPIS) based on replacement algorithm and bucket technology was proposed. In order to realize the Skyline query for incomplete data, the value of the missing attribute was replaced to the upper bound of data field and then the incomplete data was mapped into the buckets. In order to preserve the privacy of data, the range of the bucket was transformed into a prefix encoding and then the prefix encoding was loaded into Bloom filters. Thus, the query processing could be executed by the storage node without clear text of the sensor data and real range of the bucket. In order to preserve the integrity of query results, Merkle hash tree was used to construct the integrity verification code for implementing the integrity verification of query results. Theoretical analysis and simulation experiment of real dataset has confirmed the privacy and efficiency of PPIS. Compared with existing privacy-preserving Skyline query protocols-SMQ (Secure Multidimensional Query) and SSQ (Secure Skyline Query), the proposed PPIS can save the communication cost by more than 70%.