Privacy-preserving cooperative statistical analysis

Wenliang Du, Mikhail J. Atallah

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

206 Scopus citations

Abstract

The growth of the Internet opens up tremendous opportunities for cooperative computation, where the answer depends on the private inputs of separate entities. Sometimes these computations may occur between mutually untrusting entities. The problem is trivial if the context allows the conduct of these computations by a trusted entity that would know the inputs from all the participants; however if the context disallows this then the techniques of secure multiparty computation become very relevant and can provide useful solutions. Statistical analysis is a widely used computation in real life, but the known methods usually require one to know the whole data set; little work has been conducted to investigate how statistical analysis could be performed in a cooperative environment, where the participants want to conduct statistical analysis on the joint data set, but each participant is concerned about the confidentiality of its own data. We have developed protocols for conducting the statistical analysis in such a cooperative environment based on a data perturbation technique and cryptography primitives.

Original languageEnglish (US)
Title of host publicationProceedings - 17th Annual Computer Security Applications Conference, ACSAC 2001
PublisherIEEE Computer Society
Pages102-110
Number of pages9
ISBN (Electronic)0769514057
DOIs
StatePublished - 2001
Event17th Annual Computer Security Applications Conference, ACSAC 2001 - New Orleans, United States
Duration: Dec 10 2001Dec 14 2001

Publication series

NameProceedings - Annual Computer Security Applications Conference, ACSAC
Volume2001-January
ISSN (Print)1063-9527

Other

Other17th Annual Computer Security Applications Conference, ACSAC 2001
CountryUnited States
CityNew Orleans
Period12/10/0112/14/01

Keywords

  • Computer science education
  • Computer security
  • Cryptographic protocols
  • Ducts
  • Educational institutions
  • Information security
  • Internet
  • Performance analysis
  • Remuneration
  • Statistical analysis

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Software
  • Safety, Risk, Reliability and Quality

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  • Cite this

    Du, W., & Atallah, M. J. (2001). Privacy-preserving cooperative statistical analysis. In Proceedings - 17th Annual Computer Security Applications Conference, ACSAC 2001 (pp. 102-110). [991526] (Proceedings - Annual Computer Security Applications Conference, ACSAC; Vol. 2001-January). IEEE Computer Society. https://doi.org/10.1109/ACSAC.2001.991526