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.
@article{arxiv.2402.03612,
title = {Privacy risk in GeoData: A survey},
author = {Mahrokh Abdollahi Lorestani and Thilina Ranbaduge and Thierry Rakotoarivelo},
journal= {arXiv preprint arXiv:2402.03612},
year = {2024}
}