Weilin Zheng

Weilin Zheng, Bo Liu, Hong-Ning Dai et al.

Being the largest Initial Coin Offering project, EOSIO has attracted great interest in cryptocurrency markets. Despite its popularity and prosperity (e.g., 26,311,585,008 token transactions occurred from June 8, 2018 to Aug. 5, 2020), there is almost no work investigating the EOSIO token ecosystem. To fill this gap, we are the first to conduct a systematic investigation on the EOSIO token ecosystem by conducting a comprehensive graph analysis on the entire on-chain EOSIO data (nearly 135 million blocks). We construct token creator graphs, token-contract creator graphs, token holder graphs, and token transfer graphs to characterize token creators, holders, and transfer activities. Through graph analysis, we have obtained many insightful findings and observed some abnormal trading patterns. Moreover, we propose a fake-token detection algorithm to identify tokens generated by fake users or fake transactions and analyze their corresponding manipulation behaviors. Evaluation results also demonstrate the effectiveness of our algorithm.

Jieli Liu, Weilin Zheng, Dingyuan Lu et al.

Recently, many Delegated Proof-of-Stake (DPoS)-based blockchains have been widely used in decentralized applications, such as EOSIO, Tron, and Binance Smart Chain. Compared with traditional PoW-based blockchain systems, these systems achieve a higher transaction throughput and are well adapted to large-scale scenes in daily applications. Decentralization is a key element in blockchain networks. However, little is known about the evolution of decentralization in DPoS-based blockchain networks. In this paper, we conduct a systematic analysis on the decentralization of DPoS with data from up to 135,000,000 blocks in EOSIO, the first successful DPoS-based blockchain system. We characterize the decentralization evolution of the two phases in DPoS, namely block producer election and block production. Moreover, we study the voters with similar voting behaviors and propose methods to discover abnormal mutual voting behaviors in EOSIO. The analytical results show that our methods can effectively capture the decentralization evolution and abnormal voting phenomena in the system, which also have reference significance for other DPoS-based blockchains.