Privacy risk in GeoData: A survey

TL;DR

This survey reviews geomasking techniques for protecting privacy in geodata, highlighting their limitations and providing a taxonomy to guide data custodians in selecting appropriate privacy-preserving methods.

Contribution

It introduces a comprehensive taxonomy of geomasking techniques and discusses their shortcomings, offering a practical resource for privacy protection in geodata.

Findings

Current geomasking techniques have notable limitations.

The taxonomy helps classify and evaluate privacy mechanisms.

Future research directions are identified for improving privacy methods.

Abstract

With the ubiquitous use of location-based services, large-scale individual-level location data has been widely collected through location-awareness devices. The widespread exposure of such location data poses significant privacy risks to users, as it can lead to re-identification, the inference of sensitive information, and even physical threats. In this survey, we analyse different geomasking techniques proposed to protect individuals' privacy in geodata. We propose a taxonomy to characterise these techniques across various dimensions. We then highlight the shortcomings of current techniques and discuss avenues for future research. Our proposed taxonomy serves as a practical resource for data custodians, offering them a means to navigate the extensive array of existing privacy mechanisms and to identify those that align most effectively with their specific requirements.