Journal of Computer Science and Technology ›› 2022, Vol. 37 ›› Issue (4): 888-905.doi: 10.1007/s11390-022-2032-x

Special Issue: Computer Networks and Distributed Computing

• Special Section of MASS 2020-2021 • Previous Articles     Next Articles

Generous or Selfish? Weighing Transaction Forwarding Against Malicious Attacks in Payment Channel Networks

Yi Qin1 (秦毅), Qin Hu2,*, Dong-Xiao Yu1 (于东晓), Senior Member, IEEE, and Xiu-Zhen Cheng1 (成秀珍), Fellow, IEEE        

  1. 1School of Computer Science and Technology, Shandong University, Qingdao 266237, China
    2Department of Computer and Information Science, Indiana University-Purdue University Indianapolis, Indianapolis 46202, U.S.A.
  • Received:2021-11-19 Revised:2022-05-30 Accepted:2022-06-08 Online:2022-07-25 Published:2022-07-25
  • Contact: Qin Hu E-mail:qinhu@iu.edu
  • About author:Qin Hu received her Ph.D. degree in computer science from the George Washington University, Washington, in 2019. She is currently an assistant professor with the Department of Computer and Information Science, Indiana University-Purdue University Indianapolis, Indianapolis. Her research interests include wireless network, mobile security and privacy, crowdsourcing/crowdsensing, and blockchain.
  • Supported by:
    The work was partially supported by the National Key Research and Development Program of China under Grant No. 2019YFB2102600, and the National Natural Science Foundation of China under Grant Nos. 62122042, 61971269 and 61832012.

Scalability has long been a major challenge of cryptocurrency systems, which is mainly caused by the delay in reaching consensus when processing transactions on-chain. As an effective mitigation approach, the payment channel networks (PCNs) enable private channels among blockchain nodes to process transactions off-chain, relieving long-time waiting for the online transaction confirmation. The state-of-the-art studies of PCN focus on improving the efficiency and availability via optimizing routing, scheduling, and initial deposits, as well as preventing the system from security and privacy attacks. However, the behavioral decision dynamics of blockchain nodes under potential malicious attacks is largely neglected. To fill this gap, we employ the game theory to study the characteristics of channel interactions from both the micro and macro perspectives under the situation of channel depletion attacks. Our study is progressive, as we conduct the game-theoretic analysis of node behavioral characteristics from individuals to the whole population of PCN. Our analysis is complementary, since we utilize not only the classic game theory with the complete rationality assumption, but also the evolutionary game theory considering the limited rationality of players to portray the evolution of PCN. The results of numerous simulation experiments verify the effectiveness of our analysis.

Key words: blockchain; payment channel network; game theory;

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