Privacy via the Johnson-Lindenstrauss Transform

J. Priv. Confidentiality, 2013.

Cited by: 84|Views34
EI

Abstract:

Suppose that party A collects private information about its users, where each user's data is represented as a bit vector. Suppose that party B has a proprietary data mining algorithm that requires estimating the distance between users, such as clustering or nearest neighbors. We ask if it is possible for party A to publish some informat...More

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