Privacy-preserving Publication of Mobility Data with High Utility

TL;DR

This paper presents a novel method for publishing mobility data that balances privacy and utility by hiding points of interest through speed regulation and swapping trajectories at meeting points to prevent re-identification.

Contribution

It introduces a new algorithm for anonymizing mobility data by hiding points of interest and swapping trajectories at meeting points, enhancing privacy without significantly reducing data utility.

Findings

The proposed method effectively conceals points of interest.

Trajectory swapping at meeting points increases privacy protection.

The approach maintains high utility of mobility data for analysis.

Abstract

An increasing amount of mobility data is being collected every day by different means, e.g., by mobile phone operators. This data is sometimes published after the application of simple anonymization techniques, which might lead to severe privacy threats. We propose in this paper a new solution whose novelty is twofold. Firstly, we introduce an algorithm designed to hide places where a user stops during her journey (namely points of interest), by enforcing a constant speed along her trajectory. Secondly, we leverage places where users meet to take a chance to swap their trajectories and therefore confuse an attacker.