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Understanding (Mis)Behavior on the EOSIO Blockchain

Published: 09 July 2020 Publication History
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  • 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.

    References

    [1]
    2019. Bots Index. https://github.com/hashbaby-com/eos-hall-of-shame/tree/ master/bots.
    [2]
    Yuheng Huang, Haoyu Wang, Lei Wu, Gareth Tyson, Xiapu Luo, Run Zhang, Xuanzhe Liu, Gang Huang, and Xuxian Jiang. 2020. Understanding (Mis)Behavior on the EOSIO Blockchain. Proc. ACM Meas. Anal.Comput. Syst. 4, 2 (2020).

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    • (2022)The Design Blueprint for a Large-Scale Telehealth PlatformInternational Journal of Telemedicine and Applications10.1155/2022/84865082022Online publication date: 1-Jan-2022

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    Published In

    cover image ACM SIGMETRICS Performance Evaluation Review
    ACM SIGMETRICS Performance Evaluation Review  Volume 48, Issue 1
    June 2020
    110 pages
    ISSN:0163-5999
    DOI:10.1145/3410048
    Issue’s Table of Contents
    Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 09 July 2020
    Published in SIGMETRICS Volume 48, Issue 1

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    Author Tags

    1. attack detection
    2. blockchain
    3. bot account
    4. dapp
    5. eosio

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    • (2022)The Design Blueprint for a Large-Scale Telehealth PlatformInternational Journal of Telemedicine and Applications10.1155/2022/84865082022Online publication date: 1-Jan-2022

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