Method for classifying private information securely
A method for securely classifying private data x of a first party Alice using a classifier H(x) of a second party Bob. The classifier is H ( x ) = sign ( ∑ n = 1 N h n ( x ) ) , where h n ( x ) = { alpha n x T y n > Theta n beta n otherwise , alpha n , beta n and Thetan are scalar v...
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Sprache: | eng |
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Zusammenfassung: | A method for securely classifying private data x of a first party Alice using a classifier H(x) of a second party Bob. The classifier is H ( x ) = sign ( ∑ n = 1 N h n ( x ) ) , where h n ( x ) = { alpha n x T y n > Theta n beta n otherwise , alpha n , beta n and Thetan are scalar values and yn is a vector storing parameters of the classifier. Bob generates a set of N random numbers, S1, . . . , SN, such that s = ∑ n = 1 N s n , for each n=1, . . . , N, the following substeps are performed: applying a secure dot product to xTyn to obtain an for Alice and bn for Bob; applying a secure millionaire protocol to determine whether an is larger than Thetan-bn, and returning a result of an+Sn, or betan+Sn; accumulating, by Alice, the result in cn. Then, apply the secure millionaire protocol to determine whether c = ∑ n = 1 N c n is larger than s = ∑ n = 1 N s n , and returning a positive sign if true, and a negative sign if false to classify the private data x. |
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