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As one of the most popular blockchain systems, EOSIO has been widely used in decentralized applications. It achieves high transaction throughput and so-called decentralization through a delegated proof-of-stake (DPoS) consensus protocol. However, recent reports have claimed that there are voting collusion and manipulation behaviors in the DPoS consensus process of EOSIO, which may greatly reduce the decentralization, fault tolerance, and reliability of the entire system. In this chapter, we obtain data from up to 135 million EOSIO blocks and conduct data-driven decentralized analysis. Specifically, we describe the decentralized evolution of DPoS in two stages, namely block producer election and block production. In addition, we study voters with similar voting behaviors and propose a method to detect abnormal mutual voting behavior in EOSIO. The analysis results show how EOSIO gradually evolves from decentralization to oligopoly. Our method can effectively capture abnormal voting phenomena in EOSIO, which can also provide important insights for the design and maintenance of other DPoS-based blockchains.

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Evolution and Voting Behaviors in the EOSIO Networks

  • 章节

  • 发表日期：

    2025年

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  • Jieli Liu,
  • Zhe Chen,
  • Weilin Zheng,
  • Dingyuan Lu,
  • Jiajing Wu,
  • Zibin Zheng

摘要

As one of the most popular blockchain systems, EOSIO has been widely used in decentralized applications. It achieves high transaction throughput and so-called decentralization through a delegated proof-of-stake (DPoS) consensus protocol. However, recent reports have claimed that there are voting collusion and manipulation behaviors in the DPoS consensus process of EOSIO, which may greatly reduce the decentralization, fault tolerance, and reliability of the entire system. In this chapter, we obtain data from up to 135 million EOSIO blocks and conduct data-driven decentralized analysis. Specifically, we describe the decentralized evolution of DPoS in two stages, namely block producer election and block production. In addition, we study voters with similar voting behaviors and propose a method to detect abnormal mutual voting behavior in EOSIO. The analysis results show how EOSIO gradually evolves from decentralization to oligopoly. Our method can effectively capture abnormal voting phenomena in EOSIO, which can also provide important insights for the design and maintenance of other DPoS-based blockchains.