QGIS Python Plugins Repository
Plugin: Differential Privacy
Methods for anonymizing data for public distribution
This QGIS Processing provider plugin implements different methods for the
anonymization of spatial data (typically point samples) with the goal of making
the data publicly available, while preserving the privacy of the individuals
whose information the dataset contains (see ).
The differential privacy algorithm is based on the algorithm outlined in 
and implemented by Konstantinos Chatzikokolakis in the Location Guard
browser extension . The grid based masking system is discussed in .
 Andrés, M.E., Bordenabe, N.E., Chatzikokolakis, K., and Palamidessi, P.
2013. 'Geo-indistinguishability: Differential Privacy for Location-Based
Systems', In the Proceedings of the 2013 ACM SIGSAC conference on Computer
and Communications Security (CCS'13). New York, New York, USA: ACM Press,
 Dwork, C. & Roth, A., 2014. The Algorithmic Foundations of Differential
Privacy. Foundations and Trends® in Theoretical Computer Science, 9(3-4),
 Seidl, D.E., Jankowski, P. & Tsou, M.-H., 2015. Privacy and spatial
pattern preservation in masked GPS trajectory data. International Journal of
Geographical Information Science, 30(4), pp.785–800.
Toucan by Lane F. Kinkade from the Noun Project
- Henry Walshaw
- statistics , metadata , point , analysis
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- Code repository
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