Collection, usage and privacy of mobility data in the enterprise and public administrations

TL;DR

This paper explores how enterprises and public administrations handle mobility data, focusing on privacy practices, the trade-offs involved, and the gap between research and real-world implementation.

Contribution

It provides an empirical analysis of current privacy practices in mobility data handling through expert interviews and categorizes their purposes, sources, and methods.

Findings

Practitioners often use privacy methods that do not meet differential privacy standards.

There is a significant gap between research-level privacy techniques and real-world implementations.

The study identifies privacy needs and mobility characteristics relevant for future evaluations.

Abstract

Human mobility data is a crucial resource for urban mobility management, but it does not come without personal reference. The implementation of security measures such as anonymization is thus needed to protect individuals' privacy. Often, a trade-off arises as such techniques potentially decrease the utility of the data and limit its use. While much research on anonymization techniques exists, there is little information on the actual implementations by practitioners, especially outside the big tech context. Within our study, we conducted expert interviews to gain insights into practices in the field. We categorize purposes, data sources, analysis, and modeling tasks to provide a profound understanding of the context such data is used in. We survey privacy-enhancing methods in use, which generally do not comply with state-of-the-art standards of differential privacy. We provide groundwork for further research on practice-oriented research by identifying privacy needs of practitioners and extracting relevant mobility characteristics for future standardized evaluations of privacy-enhancing methods.