Understanding (Mis)Behavior on the EOSIO Blockchain

© 2020 Copyright is held by the owner/author(s). 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

A GRAPH-BASED INVESTIGATION OF BITCOIN TRANSACTIONS

Part 2: INTERNET CRIME INVESTIGATIONSInternational audienceThe Bitcoin global cryptocurrency system has been the subject of several criminal cases. The Bitcoin network is a peer-to-peer system that has participants from all over the Internet. The Bitcoin protocol requires participating nodes to retain and update all transaction records; this ensures that all Bitcoin activities are accessible from a consistent transaction history database. This chapter describes a graph-based method for analyzing the identity clustering and currency flow properties of Bitcoin transactions. The method, which is scalable to large Bitcoin graphs, focuses on transactions relevant to criminal cases such as Mt. Gox. The analysis, which is performed on two years of Bitcoin transaction data, provides insights into the nature of anonymity provided by Bitcoin and how currency flows between selected users and communities of users