On the profitability of selfish blockchain mining under consideration of ruin

Mining blocks on a blockchain equipped with a proof of work consensus protocol is well-known to be resource-consuming. A miner bears the operational cost, mainly electricity consumption and IT gear, of mining, and is compensated by a capital gain when a block is discovered. This paper aims at quantifying the profitability of mining when the possible event of ruin is also considered. This is done by formulating a tractable stochastic model and using tools from applied probability and analysis, including the explicit solution of a certain type of advanced functional differential equation. The expected profit at a future time point is determined for the situation when the miner follows the protocol as well as when he/she withholds blocks. The obtained explicit expressions allow to analyze the sensitivity with respect to the different model ingredients and to identify conditions under which selfish mining is a strategic advantage.

[1]  Cyril Grunspan,et al.  On Profitability of Trailing Mining , 2018, ArXiv.

[2]  Józef Banas,et al.  On solutions of a neutral differential equation with deviating argument , 2006, Math. Comput. Model..

[3]  Cyril Grunspan,et al.  On profitability of block withholding strategies , 2019, PERV.

[4]  Joshua A. Kroll,et al.  The Economics of Bitcoin Mining, or Bitcoin in the Presence of Adversaries , 2013 .

[5]  Avraham Adler,et al.  Lambert-W Function , 2015 .

[6]  Cyril Grunspan,et al.  On profitability of stubborn mining , 2018, ArXiv.

[7]  T. Jankowski First-order impulsive ordinary differential equations with advanced arguments , 2007 .

[8]  Hal L. Smith,et al.  An introduction to delay differential equations with applications to the life sciences / Hal Smith , 2010 .

[9]  Meni Rosenfeld,et al.  Analysis of Bitcoin Pooled Mining Reward Systems , 2011, ArXiv.

[10]  Holger Paul Keeler,et al.  Bitcoin blockchain dynamics: The selfish-mine strategy in the presence of propagation delay , 2015, Perform. Evaluation.

[11]  P. Goffard Fraud risk assessment within blockchain transactions , 2019, Advances in Applied Probability.

[12]  Satoshi Nakamoto Bitcoin : A Peer-to-Peer Electronic Cash System , 2009 .

[13]  Meni Rosenfeld,et al.  Analysis of Hashrate-Based Double Spending , 2014, ArXiv.

[14]  C. Lefèvre,et al.  Boundary crossing of order statistics point processes , 2017 .

[15]  Søren Asmussen,et al.  Ruin probabilities , 2001, Advanced series on statistical science and applied probability.

[16]  Kartik Nayak,et al.  Stubborn Mining: Generalizing Selfish Mining and Combining with an Eclipse Attack , 2016, 2016 IEEE European Symposium on Security and Privacy (EuroS&P).

[17]  Erhan Bayraktar,et al.  ON OPTIMAL DIVIDENDS IN THE DUAL MODEL , 2013, ASTIN Bulletin.

[18]  Emin Gün Sirer,et al.  Majority Is Not Enough: Bitcoin Mining Is Vulnerable , 2013, Financial Cryptography.

[19]  Florin Avram,et al.  Erlangian Approximations for Finite-Horizon Ruin Probabilities , 2002, ASTIN Bulletin.

[20]  Cyril Grunspan,et al.  On profitability of selfish mining , 2018, ArXiv.

[21]  Jeffrey S. Rosenschein,et al.  Bitcoin Mining Pools: A Cooperative Game Theoretic Analysis , 2015, AAMAS.

[22]  Holger Paul Keeler,et al.  Block arrivals in the Bitcoin blockchain , 2018, ArXiv.

[23]  Aviv Zohar,et al.  Optimal Selfish Mining Strategies in Bitcoin , 2015, Financial Cryptography.

[24]  C. J. Vanegas,et al.  On the solution of differential equations with delayed and advanced arguments. , 2005 .