TY - JOUR
T1 - Characterizing Trust and Resilience in Distributed Consensus for Cyberphysical Systems
AU - Yemini, Michal
AU - Nedic, Angelia
AU - Goldsmith, Andrea
AU - Gil, Stephanie
N1 - Funding Information:
This work was supported by the National Science Foundation under CAREER Grant #2114733, in part by the Alfred P. Sloan Fellowship, in part by the Office of Naval Research under Grant N000141512527, and in part by the Air Force Office of Scientific Research under Grant FA 8750-20-2-0504.
Publisher Copyright:
© 2004-2012 IEEE.
PY - 2022/2/1
Y1 - 2022/2/1
N2 - 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.
AB - 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.
KW - Agents' trust values
KW - Byzantine agents
KW - Consensus systems
KW - Cyberphysical systems (CPSs)
KW - Malicious agents
KW - Resilience
UR - http://www.scopus.com/inward/record.url?scp=85112134561&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85112134561&partnerID=8YFLogxK
U2 - 10.1109/TRO.2021.3088054
DO - 10.1109/TRO.2021.3088054
M3 - Article
AN - SCOPUS:85112134561
SN - 1552-3098
VL - 38
SP - 71
EP - 91
JO - IEEE Transactions on Robotics
JF - IEEE Transactions on Robotics
IS - 1
ER -