An Accurate Analytical Model for A Proof-of-Work Blockchain with Multiple Selfish Miners
Shengwei Wang, Show‐Shiow Tzeng · 2024
In a Proof-of-Work blockchain with multiple selfish miners, can we accurately and efficiently calculate the reward earned by each miner? The problem is fundamental but difficult to be solved since the miners interact with each other dynamically. This paper proposes an accurate analytical model of a Proof-of-Work blockchain with multiple selfish miners and the earned rewards can be obtained via closed-form expressions. Compared to the simulation results, our proposed analytical model is able to yield accurate calculation of the reward earned by each miner. In most situations, the differences are less than 5%. We also show that our proposed analytical model performs closer to the simulation results than some previous approaches do. The analytical model can be easily extended to a blockchain with more than two selfish miners. Therefore, our proposed analytical model provides a theoretical framework for future researches on various selfish mining strategies.