The Structuralization of Corruption by Deepfake Technology and Normative Responses : Focusing on Case Analyses

Deepfake technology, by enabling the generation of highly realistic synthetic audiovisual content, poses a fundamental threat to the credibility of information and the integrity of public trust. This study explores how deepfake technology can be exploited not merely as a tool of misinformation but as a systemic enabler of corruption through concealment and justification. By analyzing cases from the political, administrative-judicial, and corporate sectors, this study investigates the structural risks posed by deepfakes and evaluates the effectiveness of current legal and policy frameworks in South Korea and abroad. Findings indicate that the existing Korean legal response—centered on the Public Official Election Act, Information and Communications Network Act, and the Criminal Act—remains fragmented and reactive. Critical deficiencies include the absence of real-time detection systems, institutional collaboration protocols, and normative acceptance of AI-based detection tools. In contrast, the United States, the European Union, and international organizations such as the OECD and UNICRI are increasingly adopting anticipatory and multilayered governance frameworks. Based on these insights, this study proposes three strategic directions: a structural control approach to deepfake-driven corruption, legal institutionalization of AI detection technologies, and the establishment of agile administrative-judicial collaboration systems. This research contributes to the normative reconstruction of anti-corruption governance in the age of AI-generated content and highlights the urgent need for integrated regulatory mechanisms to safeguard democratic and legal institutions from technologically advanced threats.