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Secure Computation and the Combinatorics of Hidden Diversity

Explore the intertwining of hidden diversity and secure multiparty computation in modeling corruption diversity and resource-based corruptions. Learn about adversary goals, combinatorial games, and candidate functions. Unleash the power of information-effort-preserving functions in this groundbreaking work.

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Secure Computation and the Combinatorics of Hidden Diversity

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  1. Secure Computation and theCombinatorics of Hidden Diversity Juan Garay (AT&T Research) David Johnson (AT&T Research) Aggelos Kiayias (U. Athens) Moti Yung (Google)

  2. Prover Verifier Resource-based Corruptions • Adversaries corrupt parties... …for FREE! Hidden Diversity and Secure Multiparty Computation

  3. Resource-based Corruptions (cont’d) Our new questions: • How much does corruption cost? • Different parties may require different “resources” to get corrupted • Can “anonymity” be used to raise those costs? Hidden Diversity and Secure Multiparty Computation

  4. A focal point : Corruption diversity How to model corruption diversity? • Given that corruptions happen in different ways and based on different parameters, they can require a different amount of resources

  5. Resource-based corruptions Budget b (with “tokens”) Adversary’s Goal : s5 s2 s1 s3 s4

  6. Hidden Diversity and Indistinguishability s5 s2 s1 s4 s3 ? Adversary will need to waste more resources for subverting the system! Suppose different parties require different resources for corruption but externally appear the same

  7. A Combinatorial Game • GIVEN: Set B1, B2, …, Bnof buckets, with bucket Bi having non-negative integer size si, and a target fraction α, 0 < α < 1. • GOAL: Fill αnof the buckets using as few balls as possible, where a bucket of size siis filled if it receives si balls. Hidden Diversity and Secure Multiparty Computation

  8. Balls and Buckets (cont’d) n = 5, α = ½,αn= 3 Hidden Diversity and Secure Multiparty Computation

  9. Balls and Buckets (cont’d) Only Feedback from Placing a Ball: “Bucket Now Full” or “Bucket Not Yet Full” How many balls? Hidden Diversity and Secure Multiparty Computation

  10. In this work • Framework for realization of above abstraction • Computational corruptions • Sufficient conditions for abstraction • Information-Effort-Preserving (IEP) functions • Hardness Indistinguishability • Exact Hardness Hidden Diversity and Secure Multiparty Computation

  11. Candidate Functions • Random oracle • Exponentiation • f : Zq → S; q: λ-bit prime number; S: (generic) multiplicative group • Multiplication • fmult :Pλx Pλ → N Hidden Diversity and Secure Multiparty Computation

  12. In this work • Framework for realization of above abstraction • Computational corruptions • Sufficient conditions for abstraction • Information-Effort-Preserving (IEP) functions • Hardness Indistinguishability • Exact Hardness • Much is to be gained : MPC • Security: unboundedadditional adversarial effort • Efficiency: force corruption threshold to drop from 1/2 to 1/3, and run information-theoretic MPC protocol Hidden Diversity and Secure Multiparty Computation

  13. Thanks!

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