Sensitivity-Based Optimization for Blockchain Selfish Mining

In this paper, we provide a novel dynamic decision method of blockchain selfish mining by applying the sensitivity-based optimization theory. Our aim is to find optimal blockchain-pegged policy dishonest pool. To study attacks, two pools designed means different competitive criterions, where honest pool follows two-block leading criterion, while modification criterion through using policy. policy, set up policy-based continuous-time Markov process and analyze some key factors. Based on this, discuss monotonicity optimality long-run average profit with respect reward prove structure We hope methodology results derived in paper can shed light research attacks mining.