A non-parametric approach to identifying anomalies in Bitcoin mining

• Eduardo Augusto de Medeiros Silva UFU
• Ivan da Silva Sendin UFU

DOI: https://doi.org/10.5753/sbseg_estendido.2024.241602

Resumo

Selfish Mining is an attack on the proof-of-work-based cryptocurrency consensus mechanism, enabling attackers to gain more than their fair share of rewards. Its existence indicates that the Nakamoto consensus is not incentive compatible and could jeopardize blockchain security. Recently, a method employing the Z-Score to detect selfish mining was proposed. This paper introduces a non-parametric statistical technique to identify traces of selfish miners on the blockchain without assuming any specific statistical distribution for the analyzed data. Additionally, the applicability of this type of analysis is discussed.

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