TY - JOUR
T1 - Secure cloud computing algorithms for discrete constrained potential games
AU - Lu, Yang
AU - Zhu, Minghui
N1 - Funding Information:
★★ This work was partially supported by ARO W911NF-13-1-0421 (MTUhRisI)waonrdk NwSaFs pgarartnitalClyNsSu-1p5p0o5r6te6d4.by ARO W911NF-13-1-0421 This work was partially supported by ARO W911NF-13-1-0421 (MURI) and NSF grant CNS-1505664.
PY - 2015/10/1
Y1 - 2015/10/1
N2 - In this paper, we study secure cloud computing problem for a class of discrete constrained potential games. In the games, certain functions are confidential for the system operator and not disclosed to any other participant. Meanwhile, each agent is unwilling to disclose its private functions and states to any other participant. By utilizing reinforcement learning and homomorphic encryption, we propose a distributed algorithm where (i) both the confidentiality for the system operator and the privacy for the agents are protected; (ii) the convergence to Nash equilibria is formally ensured.
AB - In this paper, we study secure cloud computing problem for a class of discrete constrained potential games. In the games, certain functions are confidential for the system operator and not disclosed to any other participant. Meanwhile, each agent is unwilling to disclose its private functions and states to any other participant. By utilizing reinforcement learning and homomorphic encryption, we propose a distributed algorithm where (i) both the confidentiality for the system operator and the privacy for the agents are protected; (ii) the convergence to Nash equilibria is formally ensured.
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U2 - 10.1016/ifacol.2015.10.327
DO - 10.1016/ifacol.2015.10.327
M3 - Conference article
AN - SCOPUS:84992530154
SN - 2405-8963
VL - 28
SP - 180
EP - 185
JO - IFAC-PapersOnLine
JF - IFAC-PapersOnLine
IS - 22
T2 - 5th IFAC Workshop on Distributed Estimation and Control in Networked Systems, NecSys 2015
Y2 - 10 September 2015 through 11 September 2015
ER -