Characterizing Trust and Resilience in Distributed Consensus for Cyberphysical Systems
Characterizing Trust and Resilience in Distributed Consensus for Cyberphysical Systems
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DOI：
10.1109/tro.2021.3088054
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发表时间：
2021-03
影响因子：
7.8
通讯作者：
M. Yemini;Angelia Nedi'c;A. Goldsmith;Stephanie Gil
中科院分区：
文献类型：
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作者：
M. Yemini;Angelia Nedi'c;A. Goldsmith;Stephanie Gil
这项工作考虑了有弹性共识的问题，其中可以使用信任的随机值。具体而言，当存在指代理之间信任的其他信息时，我们得出一个统一的数学框架来表征收敛，共识偏离真实共识值以及预期的收敛速度。我们表明，在随机信任值和共识协议上的某些条件下：首先，即使恶意药物构成了网络连接的一半以上，也可能确定与共同限制值的收敛是可能的；其次，融合极限的偏差与没有攻击的情况，即真正共识值，可以以呈指数接近1的概率来界定；几乎可以肯定地，在有限的时间内可以实现第三个正确的恶意和合法代理分类。此外，预期的收敛速率是指数的函数，这是代理之间信任观察的质量的函数。
This work considers the problem of resilient consensus, where stochastic values of trust between agents are available. Specifically, we derive a unified mathematical framework to characterize convergence, deviation of the consensus from the true consensus value, and expected convergence rate, when there exists additional information of trust between agents. We show that under certain conditions on the stochastic trust values and consensus protocol: First, almost sure convergence to a common limit value is possible even when malicious agents constitute more than half of the network connectivity; second, the deviation of the converged limit, from the case where there is no attack, i.e., the true consensus value, can be bounded with probability that approaches 1 exponentially; and third correct classification of malicious and legitimate agents can be attained in finite time almost surely. Furthermore, the expected convergence rate decays exponentially as a function of the quality of the trust observations between agents.