Have a look at:

MP Armstrong, Rushton G, Zimmerman DL. Geographically masking health data to preserve confidentiality. Stat Med.1999; 18:497–525.

(citation, full text)

They discuss different 'geo-masks' for point data including displacement, rotation, random perturbation and aggregation. Although they don't discuss specific technical solutions on how to implement it, there are useful pointers to information on what you gain/loose with every approach.

For more theoretical considerations have a look at my answer to the question on similar topic.

Have a look at:

MP Armstrong, Rushton G, Zimmerman DL. Geographically masking health data to preserve confidentiality. Stat Med.1999; 18:497–525.

(citation, full text)

They discuss different 'geo-masks' for point data including displacement, rotation, random perturbation and aggregation. Although they don't discuss specific technical solutions on how to implement it, there are useful pointers to information on what you gain/loose with every approach.

For more theoretical considerations have a look at my answer to the question on similar topic.