Novel Bribery Mining Attacks: Impacts on Mining Ecosystem and the “Bribery Miner's Dilemma” in the Nakamoto-Style Blockchain System
Junjie Hu, Huan Yan, Chunxiang Xu · IEEE Transactions on Dependable and Secure Computing · 2025
Mining attacks allow adversaries to obtain a disproportionate share of the mining reward by deviating from the honest mining strategy in the Bitcoin system. Among them, the most well-known are selfish mining (SM), block withholding (BWH), fork after withholding (FAW) and bribery mining. In this paper, we propose two novel mining attacks: bribery semiselfish mining (BSSM) and bribery stubborn mining (BSM). Unlike prior work (e.g., selfish mining, block withholding), these attacks integrate bribery mechanisms to strategically influence miner behavior, leading to a 6% higher relative extra reward for adversaries in BSSM compared to semi-selfish mining and a 2% increase in BSM compared to selfish mining. This creates a novel “bribery miner's dilemma” where target miners face a Nash equilibrium conflict: individually optimal to accept bribes, but globally optimal to reject them, directly impacting the decentralization and reward distribution of the mining ecosystem. Furthermore, quantitative analysis and simulation have verified our theoretical analysis. We propose practical measures to mitigate more advanced mining attack strategies based on bribery mining and provide new ideas for addressing bribery mining attacks in the future. However, how to completely and effectively prevent these attacks is still needed on further research.