Enhancing Real-Time Traffic Data Sharing: A Differential Privacy-Based Scheme with Spatial Correlation

Junqing Le, Bowen Xing, Di Zhang () and Dewen Qiao
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Junqing Le: College of Computer Science, Chongqing University, Chongqing 400044, China
Bowen Xing: College of Computer Science, Chongqing University, Chongqing 400044, China
Di Zhang: College of Computer Science, Chongqing University, Chongqing 400044, China
Dewen Qiao: College of Computer Science, Chongqing University, Chongqing 400044, China

Mathematics, 2024, vol. 12, issue 11, 1-21

Abstract: The real-time sharing of traffic data can offer improved services to users and timely respond to environmental changes. However, this data often involves individuals’ sensitive information, raising substantial privacy concerns. It is imperative to find ways to protect the privacy of the shared traffic data while maintaining its ongoing data utility. In this paper, a Differential Privacy-based scheme with Spatial Correlation for Real-time traffic data (named as DP-SCR) is proposed. DP-SCR not only ensures the high data utility of shared traffic data, but also provides strong privacy protection. Specifically, DP-SCR is designed to adhere to w -event ε -differential privacy, ensuring a high level of privacy protection. Subsequently, a novel adaptive allocation based on spatial correlation prediction is proposed to optimize the privacy budget allocation in differential privacy. In addition, a feasible dynamic clustering algorithm is developed to minimize the relative perturbation error, which further improves the quality of shared data. Finally, the analyses demonstrate that DP-SCR provides w -event privacy for the shared data of each section, and the spatial correlation is a more pronounced characteristic of the traffic data than other characteristics. Meanwhile, experiments conducted on real-world data show that the MAR and MER of the predicted data in DP-SCR are smaller than those in other baseline DP-based schemes. It indicates that the DP-SCR scheme proposed in this paper can provide more accurate shared data.

Keywords: traffic data sharing; privacy protection; differential privacy; adaptive allocation; spatial correlation (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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