Secure cloud computing algorithms for discrete constrained potential games

Yang Lu, Minghui Zhu

    Research output: Contribution to journalConference articlepeer-review

    4 Scopus citations


    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.

    Original languageEnglish (US)
    Pages (from-to)180-185
    Number of pages6
    Issue number22
    StatePublished - Oct 1 2015
    Event5th IFAC Workshop on Distributed Estimation and Control in Networked Systems, NecSys 2015 - Philadelphia, United States
    Duration: Sep 10 2015Sep 11 2015

    All Science Journal Classification (ASJC) codes

    • Control and Systems Engineering


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