Exploring the Methods and the Need for Data Anonymization of Species Locational Data

Authors

  • Jason Huang St. George's school
  • Linlin St.John’s School, BC, Canada
  • Kelly
  • Kevin Elgin Park Secondary School, BC, Canada
  • Sean Mulgrave School

DOI:

https://doi.org/10.47611/jsrhs.v13i3.6930

Keywords:

biodiversity, artificial intelligent

Abstract

Our research provides datasets on different national parks and the different species that were seen there before. The names of the national park, as well as the scientific and common name of each species studied, are provided at the top of each dataset..The datasets give better understanding on how we can sustain the biodiversity of specific areas. While creating our method of collecting data, we encountered problems involving data being taken by unauthorized users for unethical actions. Our solution to that involves using geospatial masking and AI-assisted anonymization to ensure that the sensitive information of species occurrences are not shared. Data security,legal and ethical concerns,and possible threats to the regions’ biodiversity are the main factors we focused on while deciding with our method of creating the research paper and solutions to sustaining biodiversity.

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Published

08-31-2024

How to Cite

Huang, J., Li, L. ., Chin, K., Li, K. Z. ., & Choi, S. . (2024). Exploring the Methods and the Need for Data Anonymization of Species Locational Data. Journal of Student Research, 13(3). https://doi.org/10.47611/jsrhs.v13i3.6930

Issue

Section

HS Review Articles