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Geospatial Streams Publish with Differential Privacy

  • Yiwen NieEmail author
  • Liusheng Huang
  • Zongfeng Li
  • Shaowei Wang
  • Zhenhua Zhao
  • Wei Yang
  • Xiaorong Lu
Conference paper
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 201)

Abstract

Continuous releasing geospatial data is benefiting numerous areas, such as information push service, traffic scheduling and task assignment in crowdsourcing, etc. This kind of data is generated by people using positioning service in daily life, from which much sensitive information can be derived. Differential privacy is a strong theoretical and practical tool to provide protection; it has already been used on streams composing by datasets with fixed attributes. However, there is limited work on geospatial stream releasing with dynamic scopes for the requirement of accurate query. In this paper, aiming at achieving privacy protection of real-time geospatial synopsis with high utility, we introduce a method, called Realtime Geospatial Publish (RGP), which adopts differential privacy to geospatial stream with a new structure k-memo. We prove the privacy and utility of RGP theoretically and show the improvement of utility by experimental comparison with existing approaches on real datasets.

Keywords

Differential privacy Geospatial partition Streams Location 

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Copyright information

© ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2017

Authors and Affiliations

  • Yiwen Nie
    • 1
    Email author
  • Liusheng Huang
    • 1
  • Zongfeng Li
    • 1
  • Shaowei Wang
    • 1
  • Zhenhua Zhao
    • 1
  • Wei Yang
    • 1
  • Xiaorong Lu
    • 1
  1. 1.University of Science and Technology of ChinaHefeiChina

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