AI와 블록체인을 활용한 가상자산 범죄 수사 프레임워크에 관한 개념적 연구

The rapid expansion of the cryptocurrency market has significantly reshaped the global financial ecosystem while simultaneously creating new and complex avenues for criminal exploitation. Crimes involving cryptocurrencies are increasing in scale and sophistication, often eluding traditional investigative techniques due to the decentralized, anonymous, and transnational nature of blockchain transactions. In response, this study proposes a conceptual framework that integrates Artificial Intelligence (AI) technologies across the five core phases of cryptocurrency crime investigation: preliminary investigation, case registration, formal investigation, prosecutorial transfer, and case closure. Drawing upon a comprehensive review of recent academic literature and technical industry reports, the paper identifies ten key application areas of AI across investigative stages—ranging from anomaly detection and blockchain transaction analysis, to automated investigation report generation and cyber threat early warning. Given the sensitive nature of investigations and the limited disclosure of AI implementation details, empirical research has been constrained despite the increasing adoption of AI by international investigative agencies. This study, therefore, adopts a literature-based analytical approach as a feasible alternative to empirical field research. By synthesizing current research trends and technological advancements, the paper presents a structured, AI-driven framework designed to enhance the effectiveness and scalability of cryptocurrency crime investigations. Furthermore, it outlines practical implications for investigative agencies and offers suggestions to address methodological and infrastructural challenges that may hinder broader implementation. This work contributes a foundational model for modernizing cryptocurrency crime investigations in the AI era.