True Spatial K-Anonymity: Adaptive Areal Elimination vs. Adaptive Areal Masking

Details

• Personal Author:
  Charleux L ; Schofield K
• Description:
  Spatial anonymization of address points is critical to fields such as public health. There have been recent concerns about applications of geomasks that did not guarantee the level of k-anonymity theoretically expected. An analysis of the problem and a potential solution were previously proposed: Adaptive Areal Elimination (AAE). The present paper expands on AAE and proposes a modified version, Adaptive Areal Masking (AAM). A benchmark comparison of both methods is conducted, which shows that AAM outperforms AAE in most configurations tested. The discussion attempts to identify the application cases for which AAE might still be preferable and addresses documentation needs with both methods. [Description provided by NIOSH]
• Subjects:
  Geographic Information Systems Occupational Health Public Health Safety
• Keywords:
  Author Keywords: Geomasking Geographic Information Systems Geostatistics K-anonymity Mathematical Models Privacy Public Health Spatial Aggregation Spatial Anonymization
• ISSN:
  1523-0406
• Document Type:
  Text
• Funding:
  Grant
• Genre:
  Journal Article
• Place as Subject:
  Minnesota ; New York ; OSHA Region 2 ; OSHA Region 5
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Topic:
  Workplace Safety & Health
• Location:
  North America
• Volume:
  47
• Issue:
  6
• NIOSHTIC Number:
  nn:20068337
• Citation:
  Cartogr Geogr Inf Sci 2020 Nov; 47(6):537-549
• Contact Point Address:
  Laure Charleux, Department of Geography, University of Minnesota, Duluth, MN, United States
• Email:
  lcharleu@d.umn.edu
• Federal Fiscal Year:
  2021
• Performing Organization:
  University of Minnesota Twin Cities
• Peer Reviewed:
  True
• Start Date:
  20050701
• Source Full Name:
  Cartography and Geographic Information
• End Date:
  20250630
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:43b18463eb7e493223356ae4687e8c0f08d779a2672acec670a44571e87e95f75518eaf62b4197834424bf78426e4441b3a32f950e8daa220660b953def33930
• Download URL:
  https://stacks.cdc.gov/view/cdc/230504/cdc_230504_DS1.pdf
• File Type:
  [PDF - 3.99 MB ]