Alert Interaction Service Design for AI Face Swap Video Scams

This study examines the design of an early warning service for artificial intelligence(AI)video face-swapping scams, aiming to increase users ‘awareness of this new type of fraud. With the development of generative AI technologies, such as ChatGPT and Stable Diffusion, AI video face-swapping fraud is gradually becoming a new problem that threatens the security of personal property and privacy. The study adopts a quantitative research method to analyze the factors affecting the interaction willingness of users of AI video face-swapping fraud alert services through questionnaires, and constructs a model of influencing factors based on the technology acceptance model. The results of the study show that perceived usefulness, perceived ease of use and risk perception have a significant positive effect on user interaction willingness, which in turn significantly affects user interaction behavior. The study also suggests optimization directions for interface design, including simplifying the operation process and clearly presenting the information hierarchy. The results of the study are of great significance for designing more effective AI video face-swapping fraud alert services, which can help improve users’ ability to recognize, alert and protect themselves against emerging fraudulent tactics.