TY - GEN
T1 - Privacy-preserving cooperative statistical analysis
AU - Du, Wenliang
AU - Atallah, Mikhail J.
N1 - Publisher Copyright:
© 2001 IEEE.
PY - 2001
Y1 - 2001
N2 - 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.
AB - 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.
KW - Computer science education
KW - Computer security
KW - Cryptographic protocols
KW - Ducts
KW - Educational institutions
KW - Information security
KW - Internet
KW - Performance analysis
KW - Remuneration
KW - Statistical analysis
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U2 - 10.1109/ACSAC.2001.991526
DO - 10.1109/ACSAC.2001.991526
M3 - Conference contribution
AN - SCOPUS:84927517111
T3 - Proceedings - Annual Computer Security Applications Conference, ACSAC
SP - 102
EP - 110
BT - Proceedings - 17th Annual Computer Security Applications Conference, ACSAC 2001
PB - IEEE Computer Society
T2 - 17th Annual Computer Security Applications Conference, ACSAC 2001
Y2 - 10 December 2001 through 14 December 2001
ER -