Method for faster secure multiparty inner product with SPDZ
AssigneeRobert Bosch GmbH
InventorsXinxin Fan, Qingji Zheng, Jorge Guajardo Merchan
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AssigneeRobert Bosch GmbH
InventorsXinxin Fan, Qingji Zheng, Jorge Guajardo Merchan
Estimating the term…
A method for implementing a secure multiparty inner product computation between two parties using an SPDZ protocol involves having a first party and a second party compute, for i=1, . . . , k, a vector (I)=(II) based on a vector (x={x1, . . . , xN}), and a vector (w={W1, WN}), respectively, where (I)=(X2i-1X2i) (III)=W2i-1W2i, N is the total number of elements in the vectors k=N/2. The vectors (I), and (III) are securely shared between the parties. The parties then jointly compute SPDZ protocol Add([w2i], [x2i-1]) and Add([w2i], [x2i-1]) to determine shares [w2i-1+x2i] and [w2i+x2i-1] respectively, and then compute, for i=1, . . . , k, inner product shares [di] by performing SPDZ protocol Mult([w2i-1+x2i], [w2i+x2i-1]). SPDZ protocol ([Add d1], . . . , [dk], -(IV), . . . , -(V), -(VI), -, (VII)) is then performed to determine the inner product.
A method for implementing a secure multiparty inner product computation protocol wherein a first computational party holds a first private vector (x={x1, . . . , xN}) and a second computational party holds a second private vector (w={w1, . . . , WN}), the first private vector and the second private vector each having a number N of values, wherein the first computational party and the second computational party want to jointly compute an inner product (d) of the first private vector and the second private vector such that x1w1+ . . . +xNwN=Σi=1N xiwi, without the first computational party learning the second private vector and the second computational party learning the first private vector, the method comprising:
A multiparty computation system comprising:
Dependencies are inferred from the claim text.