Privacy-preserving kriging interpolation on partitioned data

TUĞRUL B., POLAT H.

KNOWLEDGE-BASED SYSTEMS, cilt.62, ss.38-46, 2014 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 62
  • Basım Tarihi: 2014
  • Doi Numarası: 10.1016/j.knosys.2014.02.017
  • Dergi Adı: KNOWLEDGE-BASED SYSTEMS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.38-46
  • Anahtar Kelimeler: Privacy, Kriging, Partitioned data, Prediction, Geo-statistics, DATABASES
  • Ankara Üniversitesi Adresli: Evet

Özet

Kriging is well-known, frequently applied method in geo-statistics. Its success primarily depends on the total number of measurements for some sample points. If there are sufficient sample points with measurements, kriging will reflect the surface accurately. Obtaining a sufficient number of measurements can be costly and time-consuming. Thus, different companies might obtain a limited number of measurements of the same region and want to offer predictions collaboratively. However, due to privacy concerns, they might hesitate to cooperate with each other.