TinyCasper: A privacy-preserving aggregate location monitoring system in wireless sensor networks

Chi Yin Chow, Mohamed Mokbel, Tian He

Research output: Chapter in Book/Report/Conference proceedingConference contribution

15 Citations (Scopus)

Abstract

This demo presents a privacy-preserving aggregate location monitoring system, namely, TinyCasper, in which we can monitor moving objects in wireless sensor networks while preserving their location privacy. TinyCasper consists of two main modules, in-network location anonymization and aggregate query processing over anonymized locations. In the first module, trusted wireless sensor nodes collaborate with each other to anonymize users' exact locations by a cloaked spatial region that satisfies a prespecified privacy requirement. On the other side, the aggregate query processing module collects and analyzes the cloaked spatial regions reported from the wireless sensor nodes to support aggregate and alarm queries over anonymized locations. The prototype of TinyCasper is implemented on a physical test-bed on the TinyOS/Mote platform with 39 MICAz motes.

Original languageEnglish
Title of host publicationSIGMOD 2008
Subtitle of host publicationProceedings of the ACM SIGMOD International Conference on Management of Data 2008
Pages1307-1310
Number of pages4
DOIs
Publication statusPublished - 10 Dec 2008
Externally publishedYes
Event2008 ACM SIGMOD International Conference on Management of Data 2008, SIGMOD'08 - Vancouver, BC, Canada
Duration: 9 Jun 200812 Jun 2008

Other

Other2008 ACM SIGMOD International Conference on Management of Data 2008, SIGMOD'08
CountryCanada
CityVancouver, BC
Period9/6/0812/6/08

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Keywords

  • Aggregate location monitoring systems
  • Aggregate query processing
  • Location anonymization
  • Location privacy
  • Wireless sensor networks

ASJC Scopus subject areas

  • Software
  • Information Systems

Cite this

Chow, C. Y., Mokbel, M., & He, T. (2008). TinyCasper: A privacy-preserving aggregate location monitoring system in wireless sensor networks. In SIGMOD 2008: Proceedings of the ACM SIGMOD International Conference on Management of Data 2008 (pp. 1307-1310). [1376762] https://doi.org/10.1145/1376616.1376762