【摘要】 近年来,群智感知网络作为一种新型的感知模式,已成为当前的研究热点之一.数据请求者将感知任务分发到各地区的用户,用户根据任务要求将采集到的感知数据上传到数据中心,并由数据中心返回到数据请求者.为了保护数据隐私并减少数据在传输过程的通信开销,本文基于Huang等人提出的支持密文比较的同态加密方案,设计了一种群智感知网络环境下支持多种数据处理功能的数据聚合方案.通过同态加密,提出的方案实现了安全数据聚合,同时由于密文可比较的性质,方案还能够实现对密文的多种处理,如密文求最值、求前N个密文、密文排序、数据分段统计等.通过感知数据处理,能够显著提高数据中心的计算利用率,同时有效减轻数据请求者的计算压力.安全分析和实验结果表明,提出的方案具有数据机密性、抗合谋攻击、匿名隐私保护和位置隐私保护等,并且数据聚合和密文处理是高效的.更多还原

【Abstract】 In recent years, crowd-sensing network has become one of the current research hotspots as a new type of sensing mode. The data requester distributes the perception task to users in various regions. The user uploads the collected perception data to the data center according to the task requirements, and the data center returns it to the data requester. In order to protect data privacy and reduce communication overhead during data transmission, based on the homomorphic encryption scheme proposed by HUANG, et al that supports ciphertext comparison, a secure data aggregation scheme is designed that supports multiple data processing functions in the crowd-sensing network environment. Through a homomorphic encryption, the proposed scheme can achieve secure data aggregation. Due to the ciphertext comparablility, the proposed scheme can also support various ciphertext processing, such as sorting, top-N query, the maximum or minimum query and data segmentation statistics. With processing on the perception data, it can greatly improve the computation utilization rate of the data center, and reduce the computation burden of the data requester efficiently.Finally, the security analysis and performance results show that the proposed scheme can ensure data confidentiality, resistance against collusion attacks, anonymous preserving, location privacy protection,efficient data aggregation and ciphertext processing.更多还原