2015Unpublished venueRequires access

On coding for secure computing

Deepesh Data, Vinod M. Prabhakaran

Open publisher page 3 citations

Abstract

In information theoretically secure multiparty computation, several mutually distrusting users want to jointly compute a function of their private data such that users do not learn any additional information about other users' data other than what they can infer from their own data and the function value they compute. In this work we consider asymptotically secure computation - where vanishing probability of error and vanishing information leakage are allowed as block lengths become large - in a three user setting, where two users have inputs and third user securely computes the output of a function on these two inputs. We provide generic lower bounds on the amount of communication required among users and the total amount of private randomness needed to compute any function in this three-user model. We also consider some examples where our bounds are tight. Our lower bounds are derived for the honest-but-curious security model and hence also apply for the malicious model.

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What this paper is about

In information theoretically secure multiparty computation, several mutually distrusting users want to jointly compute a function of their private data such that users do not learn any additional information about other users' data other than what they can infer from their own data and the function value they compute. In this work we consider asymptotically secure computation - where vanishing probability of error and vanishing information leakage are allowed as block lengths become large - in a three user setting, where two users have inputs and third user securely computes the output of a function on these two inputs. We provide generic lower bounds on the amount of communication required among users and the total amount of private randomness needed to compute any function in this three-user model. We also consider some examples where our bounds are tight. Our lower bounds are derived for the honest-but-curious security model and hence also apply for the malicious model.

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Available abstract

In information theoretically secure multiparty computation, several mutually distrusting users want to jointly compute a function of their private data such that users do not learn any additional information about other users' data other than what they can infer from their own data and the function value they compute. In this work we consider asymptotically secure computation - where vanishing probability of error and vanishing information leakage are allowed as block lengths become large - in a three user setting, where two users have inputs and third user securely computes the output of a function on these two inputs. We provide generic lower bounds on the amount of communication required among users and the total amount of private randomness needed to compute any function in this three-user model. We also consider some examples where our bounds are tight. Our lower bounds are derived for the honest-but-curious security model and hence also apply for the malicious model.

Key concepts: Randomness, Computer science, Computation, Private information retrieval, Theoretical computer science, Coding (social sciences), Secure multi-party computation, Function (biology)

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