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Volume 10 Issue 1
Jan.  2023

IEEE/CAA Journal of Automatica Sinica

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P. Y. Zhang, M. C. Zhou, C. X. Li, and A. Abusorrah, “Dynamic evolutionary game-based modeling, analysis and performance enhancement of blockchain channels,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 1, pp. 188–202, Jan. 2023. doi: 10.1109/JAS.2022.105911
Citation: P. Y. Zhang, M. C. Zhou, C. X. Li, and A. Abusorrah, “Dynamic evolutionary game-based modeling, analysis and performance enhancement of blockchain channels,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 1, pp. 188–202, Jan. 2023. doi: 10.1109/JAS.2022.105911

Dynamic Evolutionary Game-based Modeling, Analysis and Performance Enhancement of Blockchain Channels

doi: 10.1109/JAS.2022.105911
Funds:  This work was supported by the National Natural Science Foundation of China (61872006), Scientific Research Activities Foundation of Academic and Technical Leaders and Reserve Candidates in Anhui Province (2020H233), Top-notch Discipline (specialty) Talents Foundation in Colleges and Universities of Anhui Province (gxbj2020057), the Startup Foundation for Introducing Talent of NUIST, and by Institutional Fund Projects from Ministry of Education and Deanship of Scientific Research (DSR), King Abdulaziz University (KAU), Jeddah, Saudi Arabia (IFPDP-216-22)
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  • The recent development of channel technology has promised to reduce the transaction verification time in blockchain operations. When transactions are transmitted through the channels created by nodes, the nodes need to cooperate with each other. If one party refuses to do so, the channel is unstable. A stable channel is thus required. Because nodes may show uncooperative behavior, they may have a negative impact on the stability of such channels. In order to address this issue, this work proposes a dynamic evolutionary game model based on node behavior. This model considers various defense strategies’ cost and attack success ratio under them. Nodes can dynamically adjust their strategies according to the behavior of attackers to achieve their effective defense. The equilibrium stability of the proposed model can be achieved. The proposed model can be applied to general channel networks. It is compared with two state-of-the-art blockchain channels: Lightning network and Spirit channels. The experimental results show that the proposed model can be used to improve a channel’s stability and keep it in a good cooperative stable state. Thus its use enables a blockchain to enjoy higher transaction success ratio and lower transaction transmission delay than the use of its two peers.

     

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    Highlights

    • To decrease internal attacks in a blockchain channel network, a novel dynamic evolutionary game model is proposed based on its nodes’ behaviors. A defense strategy is developed, which considers attack cost and attack success rate. Among them, the attack cost is based on balances between any two nodes in a blockchain channel network. It allows nodes to resist attack behaviors at a certain ratio and at the same time decrease non-cooperation behaviors
    • To increase cooperation among nodes, the model considers the bounded rationality of nodes, which only know a part of the game state of a blockchain channel network. Each node adopts its strategy with the goal to maximize its profits. Driven by their profits, nodes prefer to cooperate instead of attacks or non-cooperation

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