GTCRJul 8, 2016

Blockchain Mining Games

arXiv:1607.02420v1271 citations
Originality Incremental advance
AI Analysis

This addresses security and incentive issues in blockchain protocols for cryptocurrency developers and users, but is incremental as it builds on existing game-theoretic models.

The paper analyzes strategic behavior in Bitcoin mining by modeling it as a stochastic game, showing that miners with small computational power follow expected protocol behavior, while those with large power deviate, leading to new Nash equilibria.

We study the strategic considerations of miners participating in the bitcoin's protocol. We formulate and study the stochastic game that underlies these strategic considerations. The miners collectively build a tree of blocks, and they are paid when they create a node (mine a block) which will end up in the path of the tree that is adopted by all. Since the miners can hide newly mined nodes, they play a game with incomplete information. Here we consider two simplified forms of this game in which the miners have complete information. In the simplest game the miners release every mined block immediately, but are strategic on which blocks to mine. In the second more complicated game, when a block is mined it is announced immediately, but it may not be released so that other miners cannot continue mining from it. A miner not only decides which blocks to mine, but also when to release blocks to other miners. In both games, we show that when the computational power of each miner is relatively small, their best response matches the expected behavior of the bitcoin designer. However, when the computational power of a miner is large, he deviates from the expected behavior, and other Nash equilibria arise.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

Your Notes