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Privacy-preserving mobility monitoring using sketches of stationary sensor readings

  • Michael Kamp
  • , Christine Kopp
  • , Michael Mock
  • , Mario Boley
  • , Michael May

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

Abstract

Two fundamental tasks of mobility modeling are (1) to track the number of distinct persons that are present at a location of interest and (2) to reconstruct flows of persons between two or more different locations. Stationary sensors, such as Bluetooth scanners, have been applied to both tasks with remarkable success. However, this approach has privacy problems. For instance, Bluetooth scanners store the MAC address of a device that can in principle be linked to a single person. Unique hashing of the address only partially solves the problem because such a pseudonym is still vulnerable to various linking attacks. In this paper we propose a solution to both tasks using an extension of linear counting sketches. The idea is to map several individuals to the same position in a sketch, while at the same time the inaccuracies introduced by this overloading are compensated by using several independent sketches. This idea provides, for the first time, a general set of primitives for privacy preserving mobility modeling from Bluetooth and similar address-based devices.

Original languageEnglish
Title of host publicationMachine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2013, Proceedings
PublisherSpringer Verlag
Pages370-386
Number of pages17
EditionPART 3
ISBN (Print)9783642409936
DOIs
StatePublished - 2013
Externally publishedYes
Event13th Joint European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2013 - Prague, Czech Republic
Duration: 23 Sep 201327 Sep 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 3
Volume8190 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference13th Joint European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2013
Country/TerritoryCzech Republic
CityPrague
Period23/09/1327/09/13

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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