This study concentrates on preserving privacy in a network of agents where each agent desires to evaluate a polynomial function over the private values of its immediate neighbors. We provide an algorithm for the exact evaluation of this function while preserving privacy of the involved agents. The solution is based on two cryptographic primitives: Paillier as a Partially Homomorphic Encryption scheme and multiplicative-additive secret sharing. The provided scheme covers a large class of polynomial functions in distributed systems. Moreover, conditions guaranteeing the privacy preservation of the private value of an agent against a set of colluding agents are derived. The simulation results demonstrate that the proposed scheme can be employed in a network to enhance privacy at the cost of extra communication and computation budgets.
翻译:这项研究的重点是保护代理人网络的隐私,每个代理人都希望对近邻的私人价值进行多面性功能评估。我们为准确评估这一功能提供算法,同时保护所涉代理人的隐私。解决方案基于两个加密原始数据:部分同质加密计划和多式秘密共享。所提供的计划涵盖分布式系统中的一大批多面性功能。此外,还得出了保证代理人与一组串通代理人保持私人价值的条件。模拟结果表明,拟议的计划可以在网络中使用,以额外的通信和计算预算为代价加强隐私。