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On the Capacity of Secure Distributed Batch Matrix Multiplication | IEEE Journals & Magazine | IEEE Xplore

On the Capacity of Secure Distributed Batch Matrix Multiplication


Abstract:

The problem of secure distributed batch matrix multiplication (SDBMM) studies the communication efficiency of retrieving a sequence of desired matrix products ${\mathbf{...Show More

Abstract:

The problem of secure distributed batch matrix multiplication (SDBMM) studies the communication efficiency of retrieving a sequence of desired matrix products {\mathbf{AB}} = ({\mathbf{A}}_{1}{\mathbf{B}}_{1},\,\,{\mathbf{A}}_{2}{\mathbf{B}}_{2},\,\,\cdots,\,\,{\mathbf{A}}_{S}{\mathbf{B}}_{S}) from N distributed servers where the constituent matrices {\mathbf{A}}=({\mathbf{A}}_{1}, {\mathbf{A}}_{2}, \cdots, {\mathbf{A}}_{S}) and {\mathbf{B}}=({\mathbf{B}}_{1}, {\mathbf{B}}_{2},\cdots,{\mathbf{B}}_{S}) are stored in X -secure coded form, i.e., any group of up to X colluding servers learn nothing about \mathbf{ A, B} . It is assumed that {\mathbf{A}}_{s}\in \mathbb {F}_{q}^{L\times K}, {\mathbf{B}}_{s}\in \mathbb {F}_{q}^{K\times M}, s\in \{1,2,\cdots, S\} are uniformly and independently distributed and \mathbb {F}_{q} is a large finite field. The rate of an SDBMM scheme is defined as the ratio of the number of bits of desired information that is retrieved, to the total number of bits downloaded on average. The supremum of achievable rates is called the capacity of SDBMM. In this work we explore the capacity of SDBMM, as well as several of its variants, e.g., where the user may already have either {\mathbf{A}} or {\mathbf{B}} available as side-information, and/or where the security constraint for either {\mathbf{A}} or {\mathbf{B}} may be relaxed. We obtain converse bounds, as well as achievable schemes for various cases of SDBMM, depending on the L, K, M, N, X parameters, and identify parameter regimes where these bounds match. In particular, the capacity for securely computing a batch of outer products of two vectors is (1-X/N)^{+} , for a batch of inner products of two (long) vectors the capacity approaches (1-2X/N)^{+} as the length of the vectors approaches infinity, and in general for sufficiently large K (e.g., K > 2\min (L,M) ), the capacity C is bounded as $(1-2X/N)^{+}\leq C < (1-X/N)^{...
Published in: IEEE Transactions on Information Theory ( Volume: 67, Issue: 11, November 2021)
Page(s): 7420 - 7437
Date of Publication: 15 September 2021

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