基于数据随机分割与同态加密认证的WSNs隐私数据融合优化方案  

An Optimization for Privacy-preserving Data Based on Stochastic Segmentation and Homomorphic in WSNs

作　　者：章忠宪[1] ZHANG Zhongxian(School of Information Engineering, Zhangzhou Institute of Technology, Zhangzhou 363000, China)

机构地区：[1]漳州职业技术学院信息工程学院

出　　处：《东莞理工学院学报》2020年第1期39-45,共7页Journal of Dongguan University of Technology

摘　　要：现有无线传感器网络的隐私数据安全融合方案中,存在着要么安全强度不高、数据完整性得不到有效保证,要么通信开销和计算负载高、融合精度低的问题。为了解决这个问题,将随机动态数据分割技术、改进的轻量级的端到端加法同态加密技术和同态MAC认证技术结合起来,提出了一种改进的隐私数据保护融合方案,不仅有效强化了隐私数据的保护强度和聚合结果的完整性,而且由于使用端到端的安全机制和动态随机数据分割技术,减少了节点的运算负载、节点的网络通信开销,提高了数据融合精度。In the existing aggregation of privacy-preserving data,either the security strength is not high and the data integrity is not effectively guaranteed,or the communication overhead and the computation load are high and the aggregation accuracy is low.In order to solve this problem,this paper has combined the encryption and authentication of homomorphic MAC with the technique of stochastic data segmentation to come up with an improved scheme of aggregation of privacy-preserving data.It not only effectively strengthens the protection strength for privacy-preserving data and the integrity of the aggregated results,but also reduces the computing load and communication overhead of nodes and improves the data fusion precision,due to the use of end-to-end security mechanisms and dynamic random data segmentation techniques.

关 键 词：数据融合 隐私数据 同态加密 数据分割 融合精度 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]