Research on Security Protection Technologies for Generative Artificial Intelligence and Data Privacy

Abstract

The widespread application of generative artificial intelligence has raised profound concerns about data privacy. This study systematically analyzed the multidimensional privacy and security risks hidden by this technology throughout the entire lifecycle of data, covering key aspects such as data collection, model training, and content generation. The study further sorted out and explored the current mainstream data privacy and security protection technology system, advocating the construction of a multi-level defense plan covering data, models, outputs, and system architecture. The continuous evolution of technology and the synergy of institutional norms have become the key to balancing technological innovation and privacy protection.