Algebraic Geometric Secret Sharing Schemes and Secure Multi-Party Computations over Small Fields
Algebraic Geometric Secret Sharing Schemes and Secure Multi-Party Computations over Small Fields
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DOI:
10.1007/11818175_31
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发表时间:
2006-08
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影响因子:
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通讯作者:
Hao Chen;R. Cramer
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文献类型:
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作者:
Hao Chen;R. Cramer
We introduce algebraic geometric techniques in secret sharing and in secure multi-party computation (MPC) in particular. The main result is a linear secret sharing scheme (LSSS) defined over a finite field, with the following properties.1. It isideal. The number of playersncan beas large as, whereCis an algebraic curveCof genusgdefined over.2. It isquasi-threshold: it ist-rejecting andt+1+2g-accepting, but not necessarilyt+1-accepting. It is thus in particular a ramp scheme. High information rate can be achieved.3. It hasstrong multiplicationwith respect to thet-threshold adversary structure, if. This is a multi-linear algebraic property on an LSSS facilitating zero-error multi-party multiplication, unconditionally secure against corruption by an activet-adversary.4. The finite fieldcan bedramatically smaller than n. This is by using algebraic curves with many-rational points. For example, for each small enoughε, there is a finite fieldsuch that for infinitely manynthere is an LSSS overwith strong multiplication satisfying.5. Shamir’s scheme, which requiresn>qand which has strong multiplication for, is a special case by takingg=0.Now consider the classical (“BGW”) scenario of MPC unconditionally secure (with zero error probability) against an activet-adversary with, in a synchronousn-player network with secure channels. By known results it now follows that there exist MPC protocols in this scenario, achieving the same communication complexities in terms of the number of field elements exchanged in the network compared with known Shamir-based solutions. However, in return for decreasing corruption tolerance by a smallε-fraction,qmay be dramatically smaller thann. This tolerance decrease is unavoidable due to properties of MDS codes. The techniques extend to other models of MPC. Results on less specialized LSSS can be obtained from more general coding theory arguments.