Resilience Analysis for Double Spending via Sequential Decision Optimization

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.