Abstract

Recently, diverse concepts originating from blockchain ideas have gained increasing popularity. One of the innovations in this technology is the use of the proof-of-work (PoW) concept for reaching a consensus within a distributed network of autonomous computer nodes. This goal has been achieved by design of PoW-based protocols with a built-in equilibrium property: If all participants operate honestly then the best strategy of any agent is also to follow the same protocol. However, there are concerns about the stability of such systems. In this context, the analysis of attack vectors, which represent potentially successful deviations from the honest behavior, turns out to be the most crucial question. Naturally, stability of a blockchain system can be assessed only by determining its most vulnerable components. For this reason, knowing the most successful attacks, regardless of their sophistication level, is inevitable for a reliable stability analysis. In this work, we focus entirely on blockchain systems which are based on the proof-of-work consensus protocols, referred to as PoW-based systems, and consider planning and launching an attack on such system as an optimal sequential decision-making problem under uncertainty. With our results, we suggest a quantitative approach to decide whether a given PoW-based system is vulnerable with respect to this type of attack, which can help assessing and improving its stability.

Highlights

  • In recent years, concepts originating from the blockchain idea have gained popularity

  • Proponent of blockchain systems argue that they can achieve the same level of certainty and security as those governed by a central authority at significantly lower costs

  • We focus exclusively on PoW-based systems to analyze their vulnerability with respect to the double-spending threat, since other blockchain systems are immune to this type of attack

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Summary

Introduction

Concepts originating from the blockchain idea have gained popularity. We focus exclusively on PoW-based systems to analyze their vulnerability with respect to the double-spending threat, since other blockchain systems (all those based on different consensus algorithms, like permissioned networks) are immune to this type of attack In this context, we examine the effect of pre-mining on the profitability of the double spending with two effects: Obviously, the success probability of the attack increases with the number of pre-mined blocks, while on the other hand, a longer mining race reduces rewards due to mining costs, i.e., whether the paying transaction must be placed immediately depends on the protocol’s the block reward policy. In the optimal stopping formulation, we show how to choose the optimal payment moment depending on the length difference between the official and secret chains, mining capacity ratio, confirming block number, and on the revenue/loss from the success/failure of the attack We upgrade this framework to a stochastic switching model and show how to decide whether it is worth attacking a given PoW-based system.

Stochastic Models in the Analysis of Blockchains
The Double-Spending Problem
Block Difference Dynamics
Decisions under Uncertainty
Attack Planning as an Optimal Stopping Problem
Attack Optimization in the Optimal Stopping Formulation
Algorithmic Solution
Attack Planning as an Optimal Switching Problem
Numerical Illustration of Optimal Stopping
Section 8.1.
Conclusions
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