We consider a private distributed multiplication problem involving N computation nodes and T colluding nodes. Shamir's secret sharing algorithm provides perfect information-theoretic privacy, while requiring an honest majority, i.e., N \ge 2T + 1. Recent work has investigated approximate computation and characterized privacy-accuracy trade-offs for the honest minority setting N \le 2T for real-valued data, quantifying privacy leakage via the differential privacy (DP) framework and accuracy via the mean squared error. However, it does not incorporate the error correction capabilities of Shamir's secret-sharing algorithm. This paper develops a new polynomial-based coding scheme for secure multiplication with an honest minority, and characterizes its achievable privacy-utility tradeoff, showing that the tradeoff can approach the converse bound as closely as desired. Unlike previous schemes, the proposed scheme inherits the capability of the Reed-Solomon (RS) code to tolerate erasures and adversaries. We utilize a modified Berlekamp-Welch algorithm over the real number field to detect adversarial nodes.
翻译:我们研究一个涉及N个计算节点与T个合谋节点的私有分布式乘法问题。Shamir秘密共享算法在满足诚实多数条件(即N ≥ 2T + 1)时可提供完善的信息论隐私保护。近期研究针对诚实少数场景(N ≤ 2T)探索了实数域数据的近似计算,通过差分隐私框架量化隐私泄露,并通过均方误差衡量计算精度,但未结合Shamir秘密共享算法的纠错能力。本文提出一种基于多项式的新型编码方案,用于实现诚实少数场景下的安全乘法,并刻画其可达的隐私-效用权衡,证明该权衡可无限逼近理论逆界。与现有方案不同,本方案继承了里德-所罗门码容忍擦除与对抗节点的能力,通过改进实数域上的Berlekamp-Welch算法实现对抗节点检测。