论文标题
最佳的战略开采,反对验证证明的加密自我选择
Optimal Strategic Mining Against Cryptographic Self-Selection in Proof-of-Stake
论文作者
论文摘要
加密自我选择是一个子例程,用于为现代综合共识方案(例如Algorand)选择领导者。在加密自我选择中,每个回合$ r $都有种子$ q_r $。在$ r $中,要求每个帐户所有者在数字上签署$ q_r $,哈希数字签名以产生凭据,然后将此凭据广播给整个网络。一个公开的功能以某种方式得分每个凭据,因此最低评分证书的分布与每个帐户拥有的股份的分布相同。播放最低得分凭据的用户是回合$ r $的领导者,其凭据成为种子$ q_ {r+1} $。此类协议打开了自私的开采样式攻击的可能性:拥有多个帐户的用户在第四回合中产生低得分的凭据,可以选择性地选择要广播的凭据,以影响$ r+1 $的种子。的确,用户可以为每种潜在种子的回合$ r+1 $预先计算其凭据,而仅广播产生最有利种子的凭据(在足够低的人以成为领导者的那些凭证中)。 我们考虑一个希望最大化他们拥有的帐户的回合的预期部分的对手。我们显示这样的对手总是会从偏离预期协议的情况下受益,而不论其控制权的比例如何。我们表征了最佳策略;首先,每当对手拥有持续超过$ 38 \%$ $的股份时,就证明存在最佳的积极复发策略。然后,我们提供马尔可夫决策过程制定以计算最佳策略。
Cryptographic Self-Selection is a subroutine used to select a leader for modern proof-of-stake consensus protocols, such as Algorand. In cryptographic self-selection, each round $r$ has a seed $Q_r$. In round $r$, each account owner is asked to digitally sign $Q_r$, hash their digital signature to produce a credential, and then broadcast this credential to the entire network. A publicly-known function scores each credential in a manner so that the distribution of the lowest scoring credential is identical to the distribution of stake owned by each account. The user who broadcasts the lowest-scoring credential is the leader for round $r$, and their credential becomes the seed $Q_{r+1}$. Such protocols leave open the possibility of a selfish-mining style attack: a user who owns multiple accounts that each produce low-scoring credentials in round $r$ can selectively choose which ones to broadcast in order to influence the seed for round $r+1$. Indeed, the user can pre-compute their credentials for round $r+1$ for each potential seed, and broadcast only the credential (among those with a low enough score to be the leader) that produces the most favorable seed. We consider an adversary who wishes to maximize the expected fraction of rounds in which an account they own is the leader. We show such an adversary always benefits from deviating from the intended protocol, regardless of the fraction of the stake controlled. We characterize the optimal strategy; first by proving the existence of optimal positive recurrent strategies whenever the adversary owns last than $38\%$ of the stake. Then, we provide a Markov Decision Process formulation to compute the optimal strategy.