Node Location Privacy Protection Based on Differentially Private Grids in Industrial Wireless Sensor Networks

Jun Wang,Shubo Liu,Rongbo Zhu,Zhaohui Cai

doi:10.3390/s18020410

Abstract

Wireless sensor networks (WSNs) are widely applied in industrial application with the rapid development of Industry 4.0. Combining with centralized cloud platform, the enormous computational power is provided for data analysis, such as strategy control and policy making. However, the data analysis and mining will bring the issue of privacy leakage since sensors will collect varieties of data including sensitive location information of monitored objects. Differential privacy is a novel technique that can prevent compromising single record benefits. Geospatial data can be indexed by a tree structure; however, existing differentially private release methods pay no attention to the concrete analysis about the partition granularity of data domains. Based on the overall analysis of noise error and non-uniformity error, this paper proposes a data domain partitioning model, which is more accurate to choose the grid size. A uniform grid release method is put forward based on this model. In order to further reduce the errors, similar cells are merged, and then noise is added into the merged cells. Results show that our method significantly improves the query accuracy compared with other existing methods.

Highlights

Recent years have witnessed the rapid development of the industrial wireless sensor networks (IWSNs), which have been introduced into the industry area to meet requirements of higher flexibility and market share, and IWSNs are becoming the key and fundamental technology of Industry 4.0 [1]
Radio modules or wireless nodes have been installed on mobile devices to raise mobility and flexibility which are ignored in traditional Wireless sensor networks (WSNs) [3]
The data analysis and mining will bring the issue of privacy leakage since a semi-credible cloud server is curious about sensitive location information of monitored objects [5]

Summary

Introduction

Recent years have witnessed the rapid development of the industrial wireless sensor networks (IWSNs), which have been introduced into the industry area to meet requirements of higher flexibility and market share, and IWSNs are becoming the key and fundamental technology of Industry 4.0 [1].In the industrial domain, mobile nodes are used in industrial systems incrementally [2]. Radio modules or wireless nodes have been installed on mobile devices to raise mobility and flexibility which are ignored in traditional WSNs [3]. IWSNs generally contain more moving nodes, such as mobile products, workers and other mobile devices [4]. The data analysis and mining will bring the issue of privacy leakage since a semi-credible cloud server is curious about sensitive location information of monitored objects [5]. To address this problem, a novel privacy protection technique called differential privacy [6] has been introduced to location privacy preservation

Methods

Results

Conclusion