We have shown the evolution on number of miners and blocks, and we also find that the revenue distribution among all miners in Ethereum is unequal. By proposing a Miner Sequence Bootstrapping(MSB) model, we are able to identify abnormal miners, in the sens the likelihood to mine consecutive blocks in a system is much larger than that of a fair distribution (given the realised share of nodes they mine). We believe that the reason why some mining pools could have abnormal continuously success rates is because they are employing the selfish mining strategy
In Proof-of-Work Blockchain-based systems, the ledger is kept consistent through some participants solving cryptopuzzles, usually referred to as block mining. Conventional wisdom asserts that the mining protocol is incentive-compatible. However, whether some strategic mining behaviors occur in practice or not, has been the subject of extensive debate. In this paper, we target this question by detecting anomalies in the statistics of consecutive blocks among several popular cryptocurrency systems. Firstly, we measure the inequality of mining revenue distribution in each system. Secondly, we propose a statistical method to identify the selfish mining (SM) behavior, a mining attack strategy posited by Eyal and Sirer in 2014. Our method is based on abnormal (statistically significant) high probability of continuously mining blocks. Finally, we extend our method to detect the mining cartels, in which miners secretly get together and share information about newly mined blocks. Our analysis will contribute to the research of fairness in cryptocurrency mining by providing evidence that the aforementioned strategic mining behaviors do take place in practice.
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