In this paper we introduce a variant of the Syndrome Decoding Problem (SDP), that we call Restricted SDP (R-SDP), in which the entries of the searched vector are defined over a subset of the underlying finite field. We prove the NP-completeness of R-SDP, via a reduction from the classical SDP, and describe algorithms which solve such new problem. We study the properties of random codes under this new decoding perspective, in the fashion of traditional coding theory results, and assess the complexity of solving a random R-SDP instance. As a concrete application, we describe how Zero-Knowledge Identification (ZK-ID) schemes based on SDP can be tweaked to rely on R-SDP, and show that this leads to compact public keys as well as significantly reduced communication costs. Thus, these schemes offer an improved basis for the construction of code-based digital signature schemes derived from identification schemes through the well-know Fiat-Shamir transformation.
翻译:在本文中,我们引入了综合症解码问题(SDP)的变体,我们称之为限制型SDP(R-SDP),在其中,搜索矢量的条目被定义为基础有限字段的一个子集。我们通过减少传统的SDP来证明R-SDP的NP完整性,并描述解决这种新问题的算法。我们在这种新的解码角度下,以传统编码理论结果的方式研究随机代码的特性,并评估随机型R-SDP实例的复杂程度。作为一个具体应用,我们描述了基于SDP的零知识识别(ZK-ID)计划如何被扭曲而依赖R-SDP,并表明这会导致压缩公用钥匙以及大幅降低通信成本。因此,这些计划为通过众所周知的Fiat-Shamir变换身份识别计划构建基于代码的数字签名计划提供了更好的基础。