Understanding (Mis)Behavior on the EOSIO Blockchain

Author:

Huang Yuheng1,Wang Haoyu1,Wu Lei2,Tyson Gareth3,Luo Xiapu4,Zhang Run1,Liu Xuanzhe5,Huang Gang5,Jiang Xuxian6

Affiliation:

1. Beijing University of Posts and Telecommunications, Beijing, China

2. Zhejiang University, Hangzhou, China

3. Queen Mary University of London, London, United Kingdom

4. The Hong Kong Polytechnic University, Hong Kong, China

5. Peking University, Beijing, China

6. PeckShield, Inc., Beijing, China

Abstract

EOSIO has become one of the most popular blockchain platforms since its mainnet launch in June 2018. In contrast to the traditional PoW-based systems (e.g., Bitcoin and Ethereum), which are limited by low throughput, EOSIO is the first high throughput Delegated Proof of Stake system that has been widely adopted by many decentralized applications. Although EOSIO has millions of accounts and billions of transactions, little is known about its ecosystem, especially related to security and fraud. In this paper, we perform a large-scale measurement study of the EOSIO blockchain and its associated DApps. We gather a large-scale dataset of EOSIO and characterize activities including money transfers, account creation and contract invocation. Using our insights, we then develop techniques to automatically detect bots and fraudulent activity. We discover thousands of bot accounts (over 30% of the accounts in the platform) and a number of real-world attacks (301 attack accounts). By the time of our study, 80 attack accounts we identified have been confirmed by DApp teams, causing 828,824 EOS tokens losses (roughly $2.6 million) in total.

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Networks and Communications,Hardware and Architecture,Software

Reference2 articles.

1. 2019. Bots Index. https://github.com/hashbaby-com/eos-hall-of-shame/tree/ master/bots. 2019. Bots Index. https://github.com/hashbaby-com/eos-hall-of-shame/tree/ master/bots.

2. Understanding (Mis)Behavior on the EOSIO Blockchain

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