Quantitative Analysis of Cryptocurrency Susceptibility: A Mathematical Benchmarking Model

The rise of cryptocurrencies has brought attention to significant security challenges, particularly the 51% attack. This study focuses on developing benchmarks to evaluate varying levels of vulnerability among cryptocurrencies. A detailed review of the literature identifies a lack of approaches having statistical rigor, leading to the development of a comprehensive susceptibility test model. The proposed model is based on key parameters extracted from existing studies and validated with additional quantitative data for accuracy and reliability. Benchmarking thresholds are determined using k-means clustering, allowing for the classification of cryptocurrencies into distinct security profiles. The analysis identifies five clusters: resilient cryptocurrencies have susceptibility scores below 0.532, while scores exceeding 1.557 indicate high vulnerability. The remaining clusters represent intermediate levels of resilience and risk. These findings contribute to a better understanding of cryptocurrency security, supporting informed investment decisions and providing a basis for future research and policy development.