Secure efficient multiparty computing of multivariate polynomials and applications

  • Authors:
  • Dana Dachman-Soled;Tal Malkin;Mariana Raykova;Moti Yung

  • Affiliations:
  • Columbia University;Columbia University;Columbia University;Google Inc. and Columbia University

  • Venue:
  • ACNS'11 Proceedings of the 9th international conference on Applied cryptography and network security
  • Year:
  • 2011

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Abstract

We present a robust secure methodology for computing functions that are represented as multivariate polynomials where parties hold different variables as private inputs. Our generic efficient protocols are fully black-box and employ threshold additive homomorphic encryption; they do not assume honest majority, yet are robust in detecting any misbehavior. We achieve solutions that take advantage of the algebraic structure of the polynomials, and are polynomial-time in all parameters (security parameter, polynomial size, polynomial degree, number of parties). We further exploit a "round table" communication paradigm to reduce the complexity in the number of parties. A large collection of problems are naturally and efficiently represented as multivariate polynomials over a field or a ring: problems from linear algebra, statistics, logic, as well as operations on sets represented as polynomials. In particular, we present a new efficient solution to the multi-party set intersection problem, and a solution to a multiparty variant of the polynomial reconstruction problem.