Compressive mechanism: Utilizing sparse representation in differential privacy

Yang D. Li, Zhenjie Zhang, Marianne Winslett, Yin Yang

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

34 Citations (Scopus)

Abstract

Differential privacy provides the first theoretical foundation with provable privacy guarantee against adversaries with arbitrary prior knowledge. The main idea to achieve differential privacy is to inject random noise into statistical query results. Besides correctness, the most important goal in the design of a differentially private mechanism is to reduce the effect of random noise, ensuring that the noisy results can still be useful. This paper proposes the compressive mechanism, a novel solution on the basis of state-of-the-art compression technique, called compressive sensing. Compressive sensing is a decent theoretical tool for compact synopsis construction, using random projections. In this paper, we show that the amount of noise is significantly reduced from O(√n) to O(log(n)), when the noise insertion procedure is carried on the synopsis samples instead of the original database. As an extension, we also apply the proposed compressive mechanism to solve the problem of continual release of statistical results. Extensive experiments using real datasets justify our accuracy claims.

Original languageEnglish
Title of host publicationWPES'11 - Proceedings of the 10th Annual ACM Workshop on Privacy in the Electronic Society
Pages177-182
Number of pages6
DOIs
Publication statusPublished - 16 Nov 2011
Event10th Annual ACM Workshop on Privacy in the Electronic Society, WPES'11 - Co-located with 18th ACM Conference on Computer and Communications Security, CCS 2011 - Chicago, IL, United States
Duration: 17 Oct 201117 Oct 2011

Publication series

NameProceedings of the ACM Conference on Computer and Communications Security
ISSN (Print)1543-7221

Other

Other10th Annual ACM Workshop on Privacy in the Electronic Society, WPES'11 - Co-located with 18th ACM Conference on Computer and Communications Security, CCS 2011
CountryUnited States
CityChicago, IL
Period17/10/1117/10/11

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Keywords

  • Compressive sensing
  • Differential privacy
  • Randomness

ASJC Scopus subject areas

  • Software
  • Computer Networks and Communications

Cite this

Li, Y. D., Zhang, Z., Winslett, M., & Yang, Y. (2011). Compressive mechanism: Utilizing sparse representation in differential privacy. In WPES'11 - Proceedings of the 10th Annual ACM Workshop on Privacy in the Electronic Society (pp. 177-182). (Proceedings of the ACM Conference on Computer and Communications Security). https://doi.org/10.1145/2046556.2046581