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Journal of Intelligent Computing

Study of the Geomasking Effects using K-Anonymity

Fiona Polzin, Ourania Kounadi
ITC-Faculty of Geoinformation and Earth Observation University of Twente, Enschede, The Netherlands., Department of Geography and Regional Research University of Vienna Austria

Abstract: The discrete spatial information set is grouped and modified the original points to arrive for the protection of Geomasks. We have developed Adaptive Voronoi Masking which relies on Adaptive Aerial Elimination (AAE) and Voronoi Masking and it serves a potential alternative. It uses the population density by establishing areas of K-anonymity in which Voronoi polygons are created. AVM uses the underlying topography and displaces data points to street intersections. This process enables the decreases the risk of false-identification since residences are not endowed with a data point. We in the work further assessed the geomasking effects of AVM by many spatial analytical results and compared with the outputs of AAE, VM, and Donut Masking (DM). We found that the VM attains the best efficiency for the mean centres whereas DM does for the median centres. DM proved to the strongest performance since its cluster ellipsoids and clustering distance are the most similar to those of the original data. Finally, we found that the AVM was ranked as 2nd in terms of data utility (i) and also outperforms all methods regarding the risk of false re-identification. AVM is found to be an advantageous technique to mask geodata which is assessed with the help of the performance combination of all the factors.

Keywords: Geoprivacy, Location Privacy, Geomasking, Adaptive Voronoi Masking, Voronoi Masking, Adaptive Aerial Elimination, Donut Geomasking, ESDA Study of the Geomasking Effects using K-Anonymity

DOI:https://doi.org/10.6025/jic/2021/12/4/107-121

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