Random projection data perturbation based privacy protection in WSNs

Zhao Ming, Wu Zheng-jiang, Hui Liu
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引用次数: 2

Abstract

Wireless sensor networks are responsible for sensing, gathering and processing the information of the objects in the network coverage area. Basic data fusion technology generally does not provide data privacy protection mechanism, and the privacy protection mechanism in health care, military reconnaissance, smart home and other areas of the application is usually indispensable. In this paper, we consider the privacy, confidentiality, and the accuracy of fusion results, and propose a data fusion algorithm for privacy preserving. This algorithm relies on the characteristics of data fusion, and uses the method of pre-distribution random number in the node to get the privacy protection requirements of the original data. Theoretical analysis shows that the malicious attacker attempts to steal the difficulty of node privacy in PPND algorithm. At the same time in the TOSSIM simulation results also show that, compared with TAG, SMART algorithm, PPND algorithm in the data traffic, the convergence accuracy of the good performance.
基于随机投影数据摄动的wsn隐私保护
无线传感器网络负责感知、采集和处理网络覆盖区域内物体的信息。基础数据融合技术一般不提供数据隐私保护机制,而隐私保护机制在医疗保健、军事侦察、智能家居等领域的应用通常是不可或缺的。本文考虑融合结果的隐私性、保密性和准确性,提出了一种保护隐私的数据融合算法。该算法依靠数据融合的特点,采用节点预分布随机数的方法,得到原始数据的隐私保护要求。理论分析表明,恶意攻击者试图窃取PPND算法中节点隐私的难度。同时在TOSSIM仿真结果中也表明,与TAG、SMART算法、PPND算法相比,在数据流量的收敛精度上表现良好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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