Title: A location privacy protection algorithm based on differential privacy in sensor network

Authors: Kaiqiang Kou; Zhaobin Liu; Hong Ye; Zhiyang Li; Weijiang Liu

Addresses: School of Information Science and Technology, Dalian Maritime University, Dalian 116000, China ' School of Information Science and Technology, Dalian Maritime University, Dalian 116000, China ' School of Information Science and Technology, Dalian Maritime University, Dalian 116000, China ' School of Information Science and Technology, Dalian Maritime University, Dalian 116000, China ' School of Information Science and Technology, Dalian Maritime University, Dalian 116000, China

Abstract: The continuous development and innovation in sensor networks has simplified the processes of data collection and transmission and has led to their widespread use. However, these processes often involve sensitive location information. Therefore, the location of a sensor should be protected for privacy reasons during data collection and transmission. In this paper, we propose a privacy protection scheme for location in a sensor network, based on differential privacy. Although the algorithm satisfies the privacy protection requirements, the accumulation of noise in the privacy protection process may decrease the utility of the data. To solve this problem, we propose a square sum error-based location privacy protection algorithm. Our algorithm can reduce the accumulation of noise, while also protecting the structure of the sensor network.

Keywords: differential privacy; sensor network; privacy protection; grid clustering.

DOI: 10.1504/IJES.2021.120257

International Journal of Embedded Systems, 2021 Vol.14 No.5, pp.432 - 442

Received: 06 Jul 2020
Accepted: 23 Aug 2020
Published online: 13 Jan 2022 *

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