# Sensitivity-Based Optimization for Blockchain Selfish Mining

arXiv: https://arxiv.org/abs/2111.07070 · HTML: https://mlsanity.com/paper/2111.07070/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 13 Nov 2021.

## Built on by (most cited first, 1 of 1)

- [Performance Evaluation, Optimization and Dynamic Decision in Blockchain Systems: A Recent Overview](https://mlsanity.com/paper/2211.15907/) (2022)

## Abstract (arXiv)

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