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Secure Computation from Random Error Correcting Codes

  • Hao Chen
  • Ronald Cramer
  • Shafi Goldwasser
  • Robbert de Haan
  • Vinod Vaikuntanathan
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4515)

Abstract

Secure computation consists of protocols for secure arithmetic: secret values are added and multiplied securely by networked processors. The striking feature of secure computation is that security is maintained even in the presence of an adversary who corrupts a quorum of the processors and who exercises full, malicious control over them. One of the fundamental primitives at the heart of secure computation is secret-sharing. Typically, the required secret-sharing techniques build on Shamir’s scheme, which can be viewed as a cryptographic twist on the Reed-Solomon error correcting code. In this work we further the connections between secure computation and error correcting codes. We demonstrate that threshold secure computation in the secure channels model can be based on arbitrary codes. For a network of size n, we then show a reduction in communication for secure computation amounting to a multiplicative logarithmic factor (in n) compared to classical methods for small, e.g., constant size fields, while tolerating \(t < ({1 \over 2} - {\epsilon}) {n} \) players to be corrupted, where ε> 0 can be arbitrarily small. For large networks this implies considerable savings in communication. Our results hold in the broadcast/negligible error model of Rabin and Ben-Or, and complement results from CRYPTO 2006 for the zero-error model of Ben-Or, Goldwasser and Wigderson (BGW). Our general theory can be extended so as to encompass those results from CRYPTO 2006 as well. We also present a new method for constructing high information rate ramp schemes based on arbitrary codes, and in particular we give a new construction based on algebraic geometry codes.

Keywords

Linear Code Secure Computation Secret Sharing Scheme Arbitrary Code Algebraic Geometry Code 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Hao Chen
    • 1
  • Ronald Cramer
    • 2
    • 4
  • Shafi Goldwasser
    • 3
    • 5
  • Robbert de Haan
    • 4
  • Vinod Vaikuntanathan
    • 5
  1. 1.Department of Computing and Information Technology, School of Information Science and EngineeringFudan UniversityShanghaiChina
  2. 2.Mathematical InstituteLeiden UniversityThe Netherlands
  3. 3.Weizmann Institute of ScienceRehovotIsrael
  4. 4.CWIAmsterdamThe Netherlands
  5. 5.MITCambridgeUSA

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