AI 中文总结
本文针对区块链审查攻击，提出引入可检测性阈值可使巨鲸奖励减少，改变均衡状态，仅靠小鱼难以发动攻击，并通过蒙特卡洛模拟在以太坊和索拉纳中验证了该结论。
AI 中文摘要
我们研究了文献[21]中提出的区块链审查攻击，该研究表明参与此攻击是一种占优策略。我们发现，通过引入特定的可检测性阈值，参与攻击会导致“巨鲸（whales，指少数拥有远超其余“小鱼（minnows）”投票权的验证者）”获得的奖励大幅减少，这改变了均衡状态：由于巨鲸不愿参与攻击，仅靠小鱼难以发动攻击。我们还通过蒙特卡洛模拟，验证了以太坊（Ethereum）和索拉纳（Solana）中巨鲸奖励减少的情况确实存在。
英文摘要
We study the blockchain censorship attack introduced in [21], which shows that joining the attack is a dominant strategy. We show that, by introducing certain detectability threshold, joining the attack can lead to strictly less reward for whales, which are defined to be a small number of validators that hold significantly more voting power than the rest (henceforth known as minnows). This leads to a change of the equilibrium: With whales unwilling to participate in the attack, it is difficult for minnows alone to launch the attack. We also perform Monte Carlo simulation to show the existence of reduction for whales' reward in Ethereum and Solana.
