Private Computation of Systematically Encoded Data with Colluding Servers

By David A. Karpuk. 2018

29 citations recorded by the source corpus.

Private Computation (PC), recently introduced by Sun and Jafar, is a generalization of Private Information Retrieval (PIR) in which a user wishes to privately compute an arbitrary function of data stored across several servers. We construct a PC scheme which accounts for server collusion, coded data, and non-linear functions. For data replicated over several possibly colluding servers, our scheme computes arbitrary functions of the data with rate equal to the asymptotic capacity of PIR for this setup. For systematically encoded data stored over colluding servers, we privately compute arbitrary functions of the columns of the data matrix and calculate the rate explicitly for polynomial functions. The scheme is a generalization of previously studied star-product PIR schemes.

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1. Sarah A. Obead
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Citations in the corpus

• Achievable Rate of Private Function Retrieval from MDS Coded Databases (2018, methodology): “In [11] a private computation scheme for polynomial functions of the data over T colluding databases is constructed by generalizing the star-product PIR scheme of [8].”