Journals
  Publication Years
  Keywords
Search within results Open Search
Please wait a minute...
For Selected: Toggle Thumbnails
Markov chain model and profit analysis of two-selfish-miner strategy in ethereum classic network
Junling WANG, Junjun BIAN, Jianian LIU, Zhiqiang XU
Journal of Computer Applications    2026, 46 (5): 1526-1533.   DOI: 10.11772/j.issn.1001-9081.2025050596
Abstract49)   HTML0)    PDF (876KB)(16)       Save

Selfish mining disrupts the normal consensus process of blockchain networks by concealing mining and delaying the release of new blocks, resulting in increased fork rate and reduced system efficiency. To quantitatively analyze the impact of selfish mining on the EThereum Classic (ETC) network under a multi-attacker environment, a Markov chain model with multiple attackers was constructed aiming at the ETC network's unique uncle block and nephew block reward mechanism, and the revenue dynamics of miners under different scenarios were quantitatively analyzed. Experimental results show that when the attacker's computing power reaches 0.3, a coordinated attack by two selfish mining pools increases the stale block rate from 26.35% to 36.21% and reduces the system throughput (Transactions Per Second (TPS)) from 20.15 to 16.44. Compared with the case of a single-selfish-miner, this attack strategy further increases the attacker's relative revenue while exacerbating the problems of harming honest miners' revenue, increasing the stale block rate, and decreasing the system efficiency. The above reveals the complex revenue mechanism of multi-attacker selfish mining and provides a theoretical and quantitative basis for designing targeted defense strategies.

Table and Figures | Reference | Related Articles | Metrics