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Blockchain Mining With Multiple Selfish Miners
IEEE Transactions on Information Forensics and Security ( IF 6.8 ) Pub Date : 2023-05-12 , DOI: 10.1109/tifs.2023.3275736
Qianlan Bai, Yuedong Xu, Nianyi Liu, Xin Wang

This paper studies a fundamental problem regarding the security of blockchain PoW consensus on how the existence of multiple misbehaving miners influences the profitability of selfish mining. Each selfish miner maintains a private chain and makes it public opportunistically for acquiring more rewards incommensurate to his Hash power. We first establish a general Markov chain model to characterize the state transition of public and private chains for Basic Selfish Mining (BSM), and derive the stationary profitable threshold of Hash power in closed form. It reduces from 25% for a single attacker to below 21.48% for two symmetric attackers theoretically, and further reduces to around 10% with eight symmetric attackers experimentally. We next explore the profitable threshold when one of the attackers performs strategic mining based on Partially Observable Markov Decision Process (POMDP) that only half of the attributes pertinent to a mining state are observable to him. An online algorithm is presented to compute the nearly optimal policy efficiently despite the large state space and high dimensional belief space. The profitable threshold is much lower for the strategic attacker. Last, we formulate a simple model of absolute mining revenue that yields an interesting observation: selfish mining is never profitable at the first difficulty adjustment period, but relies on the reimbursement of stationary selfish mining gains in future periods. The delay till being profitable of an attacker increases with the decrease of his Hash power, making blockchain miners more cautious about performing selfish mining.

中文翻译:

多个自私矿工的区块链挖矿

本文研究了关于区块链 PoW 共识安全性的一个基本问题,即多个行为不端的矿工的存在如何影响自私挖矿的盈利能力。每个自私的矿工都维护一条私有链,并机会主义地将其公开以获得与其哈希能力不相称的更多奖励。我们首先建立一个通用马尔可夫链模型来表征基本自私挖矿(BSM)的公链和私有链的状态转换,并推导封闭形式的哈希算力的平稳盈利阈值。从理论上讲,它从单个攻击者的 25% 降低到两个对称攻击者的 21.48% 以下,并在实验上进一步降低到 8 个对称攻击者的 10% 左右。接下来,我们将探讨当其中一名攻击者基于部分可观察马尔可夫决策过程 (POMDP) 执行战略挖掘时的盈利阈值,他只能观察到与挖掘状态相关的一半属性。尽管存在大状态空间和高维置信空间,但提出了一种在线算法来有效地计算接近最优的策略。对于战略攻击者来说,获利门槛要低得多。最后,我们制定了一个简单的绝对挖矿收入模型,得出了一个有趣的观察结果:自私挖矿在第一个难度调整期永远不会盈利,而是依赖于未来时期固定自私挖矿收益的补偿。攻击者获利的延迟随着其哈希算力的降低而增加,
更新日期:2023-05-12
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