Private Function Computation

Behrooz Tahmasebi, Mohammad Ali Maddah-Ali

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

In this paper, we study the problem of private function computation, where a user wants to compute a function of some inputs, using N \in \mathbb{N} servers, where the function is a private combination/composition of some K \in \mathbb{N} public basic functions {f 1 , f 2 ,., f K }. More precisely, for some inputs W m , m [1 : M], the user's goal is to calculate h\left( {{W-m}} \right) = \sum\nolimits-{j = 1}^J {{\alpha -j}} {h-j}\left( {{W-m}} \right), for some J \in \mathbb{N}, some scalers α j , j [1 : J], and some functions h j (.), j [1 : J], where each is an arbitrary compositions of the basic functions {f 1 , f 2 ,., f K }. The computation is done through a sequence of queries to N servers. In each query, the user sends an input W , which is a (possibly randomized) function of W 1:M and the answers to the previous queries, to one of the servers, and asks the server to return f k (W ), for some k [1 : K]. The servers should not obtain any information about the structure of the function h(.), i.e., the way the basic functions are combined to form h(.), from the sequence of queries they received, even if T of them collude, for some T \in \mathbb{N}.In this paper, we focus on the cases, where basic functions are linear and can be represented by (possibly large-scale) full-rank matrices, and each basic function may contribute in function h(.) for at most once. We prove that C, defined as the supremum of the number of desired computations of the basic functions, normalized by the number of queries, in asymptotic regimes of large M, satisfies the following inequality:\begin{equation∗}\min \left\{ {\left( {1 - \frac{T}{N}} \right)/\left( {1 - \frac{1}{K}} \right),\left( {1 - \frac{{T - 1}}{N}} \right)} \right\} \leq C \leq 1.\end{equation∗}The key idea is that in the proposed scheme, each server is asked to compute a specific order of basic functions, independent from the user's desired function. In addition, some random vectors are added to the inputs of the queries such that the sequence of the queries does not leak any information.

Original languageEnglish (US)
Title of host publication2020 IEEE International Symposium on Information Theory, ISIT 2020 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1118-1123
Number of pages6
ISBN (Electronic)9781728164328
DOIs
StatePublished - Jun 2020
Externally publishedYes
Event2020 IEEE International Symposium on Information Theory, ISIT 2020 - Los Angeles, United States
Duration: Jul 21 2020Jul 26 2020

Publication series

NameIEEE International Symposium on Information Theory - Proceedings
Volume2020-June
ISSN (Print)2157-8095

Conference

Conference2020 IEEE International Symposium on Information Theory, ISIT 2020
Country/TerritoryUnited States
CityLos Angeles
Period7/21/207/26/20

Bibliographical note

Publisher Copyright:
© 2020 IEEE.

Keywords

  • Private function retrieval
  • private computation
  • private information retrieval

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