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Cryptocurrency Mining Games with Economic Discount and Decreasing Rewards

Authors :
Arenas, Marcelo
Reutter, Juan
Toussaint, Etienne
Ugarte, Martín
Vial, Francisco
Vrgoč, Domagoj
Publication Year :
2020
Publisher :
Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2020.

Abstract

In the consensus protocols used in most cryptocurrencies, participants called miners must find valid blocks of transactions and append them to a shared tree-like data structure. Ideally, the rules of the protocol should ensure that miners maximize their gains if they follow a default strategy, which consists on appending blocks only to the longest branch of the tree, called the blockchain. Our goal is to understand under which circumstances are miners encouraged to follow the default strategy. Unfortunately, most of the existing models work with simplified payoff functions, without considering the possibility that rewards decrease over time because of the game rules (like in Bitcoin), nor integrating the fact that a miner naturally prefers to be paid earlier than later (the economic concept of discount). In order to integrate these factors, we consider a more general model where issues such as economic discount and decreasing rewards can be set as parameters of an infinite stochastic game. In this model, we study the limit situation in which a miner does not receive a full reward for a block if it stops being in the blockchain. We show that if rewards are not decreasing, then miners do not have incentives to create new branches, no matter how high their computational power is. On the other hand, when working with decreasing rewards similar to those in Bitcoin, we show that miners have an incentive to create such branches. Nevertheless, this incentive only occurs when a miner controls a proportion of the computational power which is close to half of the computational power of the entire network.<br />LIPIcs, Vol. 154, 37th International Symposium on Theoretical Aspects of Computer Science (STACS 2020), pages 54:1-54:16

Details

Language :
English
Database :
OpenAIRE
Accession number :
edsair.doi...........8b531435f46d568be09c5acc5ace0351
Full Text :
https://doi.org/10.4230/lipics.stacs.2020.54