mlsanityData to 14 Oct 2026

A Survey on Differential Privacy for SpatioTemporal Data in Transportation Research

arXiv 2407.15868 ↗First posted 18 Jul 2024cs.CR cs.CY cs.LGcited by 0

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Abstract (arXiv)

With low-cost computing devices, improved sensor technology, and the proliferation of data-driven algorithms, we have more data than we know what to do with. In transportation, we are seeing a surge in spatiotemporal data collection. At the same time, concerns over user privacy have led to research on differential privacy in applied settings. In this paper, we look at some recent developments in differential privacy in the context of spatiotemporal data. Spatiotemporal data contain not only features about users but also the geographical locations of their frequent visits. Hence, the public release of such data carries extreme risks. To address the need for such data in research and inference without exposing private information, significant work has been proposed. This survey paper aims to summarize these efforts and provide a review of differential privacy mechanisms and related software. We also discuss related work in transportation where such mechanisms have been applied. Furthermore, we address the challenges in the deployment and mass adoption of differential privacy in transportation spatiotemporal data for downstream analyses.

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16 of 55 references.

References · 16

  1. 2020Extracting Training Data from Large Language Modelscited by 2,189
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  6. 2020Local Differential Privacy and Its Applications: A Comprehensive Surveycited by 41
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  10. 2022Individual Privacy Accounting for Differentially Private Stochastic Gradient Descentcited by 20
  11. 2019Estimating Numerical Distributions under Local Differential Privacycited by 17
  12. 2022Data-Driven Traffic Assignment: A Novel Approach for Learning Traffic Flow Patterns Using a Graph Convolutional Neural Networkcited by 12
4 more
  1. 2014Differentially Private Algorithms for Empirical Machine Learningcited by 8
  2. 2023Classification with Partially Private Featurescited by 4
  3. 2024Traffic Control via Connected and Automated Vehicles: An Open-Road Field Experiment with 100 CAVscited by 4
  4. 2023Traffic smoothing using explicit local controllerscited by 2

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