Privacy-Preserving Kriging Interpolation on Distributed Data


TUĞRUL B., Polat H.

14th International Conference on Computational Science and Its Applications (ICCSA), Guimaraes, Portugal, 30 June - 03 July 2014, vol.8584, pp.695-708 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Volume: 8584
  • Doi Number: 10.1007/978-3-319-09153-2_52
  • City: Guimaraes
  • Country: Portugal
  • Page Numbers: pp.695-708
  • Keywords: Privacy, kriging, distributed data, prediction, geostatistics, COMPUTATION
  • Anadolu University Affiliated: Yes

Abstract

Kriging is one of the most preferred geostatistical methods in many engineering fields. Basically, it creates a model using statistical properties of all measured points in the region, where a prediction value is sought. The accuracy of the kriging model depends on the total number of measured points. Acquiring sufficient number of measurement requires so much time and budget. In some scenarios, private or governmental institutions may collect geostatistical data for the same or neighbor region. Collaboration of such organizations may build better models, if they join their data sets. However, due to financial and privacy reasons, they might hesitate to collaborate.