The Paradox of Generative Data: Ensuring Security and Privacy

Start year: 2025

Summary: The project aims to address the security and privacy challenges associated with generative data. The project will examine the current approaches and techniques for ensuring the safety and privacy of generative data, and use this knowledge to develop controllable and traceable data generation methods, new privacy protection methods, and forensic techniques. The result will be a comprehensive suite of tools and techniques for generating secure and private synthetic data, preserving individual privacy, and detecting fake data and manipulation across multiple modalities. This solution will help to ensure the security and privacy of artificial data in critical applications such as machine learning and artificial intelligence.