Demo abstract: PrOLoc: Resilient localization with private observers using partial homomorphic encryption

Amr Alanwar, Yasser Shoukry, Supriyo Chakraborty, Bharathan Balaji, Paul Martin, Paulo Tabuada, Mani Srivastava

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

14 Scopus citations

Abstract

This demo abstract presents PrOLoc, a localization system that combines partially homomorphic encryption with a new way of structuring the localization problem to enable efficient and accurate computation of a target's location while preserving the privacy of the observers.

Original languageEnglish
Title of host publicationProceedings - 2017 16th ACM/IEEE International Conference on Information Processing in Sensor Networks, IPSN 2017
PublisherAssociation for Computing Machinery, Inc
Pages257-258
Number of pages2
ISBN (Electronic)9781450348904
DOIs
StatePublished - 18 Apr 2017
Externally publishedYes
Event16th ACM/IEEE International Conference on Information Processing in Sensor Networks, IPSN 2017 - Pittsburgh, United States
Duration: 18 Apr 201720 Apr 2017

Publication series

NameProceedings - 2017 16th ACM/IEEE International Conference on Information Processing in Sensor Networks, IPSN 2017

Conference

Conference16th ACM/IEEE International Conference on Information Processing in Sensor Networks, IPSN 2017
Country/TerritoryUnited States
CityPittsburgh
Period18/04/1720/04/17

Keywords

  • Homomorphic encryption
  • Paillier cryptosystem
  • Privacy
  • Secure localization

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