Evaluating the Effectiveness of Fraud Prevention Strategies in the Cryptocurrency Ecosystem

Abstract

Ever since the emergence of Cryptocurrency in 2009, it has been thought of as the top alternative to fiat currencies. However, an increase in fraud has resulted in a significant challenge to its adoption and trust. The increase in the number of frauds is a critical concern for the industry, regulators, and users. New types of cryptocurrency fraud continue to emerge. However, the prevention strategies remain fragmented, with low consumer awareness. The proposed framework successfully mapped scam types to vulnerabilities and explained more than 90% of real-world scams using layered prevention strategies. While it highlights the gaps in the evolution of prevention and the need for layered awareness and controls, this study examines the effectiveness of fraud prevention strategies and identifies scams that exploit vulnerabilities across various layers. Starting with a chronological analysis of crypto frauds from 2009 to 2025 using the literature review of peer-reviewed papers, the study created a three-layer fraud framework comprising Infrastructure, Application, and UI. Using rule-based classification logic, such as keyword detection and conditional logic, we validated the framework against a dataset (9000 entries).