The Center for Education and Research in Information Assurance and Security (CERIAS)

The Center for Education and Research in
Information Assurance and Security (CERIAS)

Privacy-Preserving Cooperative Statistical Analysis

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Author

Wenliang Du, Mikhail Atallah

Tech report number

CERIAS TR 2003-12

Entry type

inproceedings

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 untrusted 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 multi-party computation become very relevant and can provide useful solutions. Statistic 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. In this paper we have developed protocols for conducting the statistic analysis in such kind of cooperative environment based on a data perturbation technique and cryptography primitives.

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Date

2001 – 12

Booktitle

17th Annual Computer Security Applications Conference (ACSAC)

Key alpha

Du

Pages

102-110

Affiliation

Syracuse University, Purdue University

Publication Date

2001-12-01

Language

English

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