A comparison of obfuscation methods for privacy protection: A case study using agri-environmental data in the Republic of Ireland

A major challenge of sharing spatially explicit agriculture data is to identify the trade-off between field parcel confidentiality and spatial pattern preservation. In this work, twenty-seven point-based obfuscation and evaluation methods were applied on agriculture data with a high point density. This study identified the optimal value of radiuses for Donut and Density methods to improve geoprivacy and statistical analysis accuracy. Modified AHilb and Donut-AHilb methods were developed to generate smaller and arbitrary obfuscation areas to improve location security. The Donut-AHilb method was found to be the best in spatial pattern preservation and satisfy larger k-anonymity but the risk of false identification and non-unique obfuscation were high. The term of non-unique obfuscated points was introduced which is important for static objects as two or more points might have the same obfuscated point.