Time series compressibility and privacy

Spiros Papadimitriou, Feifei Li, George Kollios, Philip S. Yu

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

85 Scopus citations

Abstract

In this paper we study the trade-offs between time series compressibility and partial information hiding and their fundamental implications on how we should introduce uncertainty about individual values by perturbing them. More specifically, if the perturbation does not have the same compressibility properties as the original data, then it can be detected and filtered out, reducing uncertainty. Thus, by making the perturbation "similar" to the original data, we can both preserve the structure of the data better, while simultaneously making breaches harder. However, as data become more compressible, a fraction of the uncertainty can be removed if true values are leaked, revealing how they were perturbed. We formalize these notions, study the above trade-offs on real data and develop practical schemes which strike a good balance and can also be extended for on-the-fly data hiding in a streaming environment.

Original languageEnglish (US)
Title of host publication33rd International Conference on Very Large Data Bases, VLDB 2007 - Conference Proceedings
EditorsJohannes Gehrke, Christoph Koch, Minos Garofalakis, Karl Aberer, Carl-Christian Kanne, Erich J. Neuhold, Venkatesh Ganti, Wolfgang Klas, Chee-Yong Chan, Divesh Srivastava, Dana Florescu, Anand Deshpande
PublisherAssociation for Computing Machinery, Inc
Pages459-470
Number of pages12
ISBN (Electronic)9781595936493
StatePublished - 2007
Externally publishedYes
Event33rd International Conference on Very Large Data Bases, VLDB 2007 - Vienna, Austria
Duration: Sep 23 2007Sep 27 2007

Publication series

Name33rd International Conference on Very Large Data Bases, VLDB 2007 - Conference Proceedings

Other

Other33rd International Conference on Very Large Data Bases, VLDB 2007
Country/TerritoryAustria
CityVienna
Period9/23/079/27/07

All Science Journal Classification (ASJC) codes

  • Hardware and Architecture
  • Information Systems and Management
  • Information Systems
  • Software

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