Talk 8A & 8B: Data Privacy in the Age of AI and Large Language Models, Li Xiong, Emory Uni., USA

Abstract As artificial intelligence (AI) and large language models (LLMs) increasingly influence every facet of our lives, ensuring the privacy of user data has become paramount. In this talk, I will review the common privacy attacks for inferring training data from a trained AI model and common defenses for building privacy-enhanced models using privacy sensitive data. I will then present our recent works and discuss open challenges related to: 1) new privacy attacks under the fine-tuning paradigm using pre-trained LLMs, and 2) end-to-end privacy defenses across the life cycle of AI and LLMs. Bio: Li Xiong is a Samuel Candler Professor of Computer Science and Biomedical Informatics at Emory University. She has a Ph.D. from Georgia Institute of Technology, an MS from Johns Hopkins University, and a BS from the University of Science and Technology of China. Her research lab, Assured Information Management and Sharing (AIMS), conducts research on trustworthy and privacy-enhancing data-driven AI solutions for healthcare, public health, and spatial intelligence. She is recognized as an IEEE fellow (2022) and AAAS fellow (2024) for her contributions on privacy-preserving and secure data sharing and analytics. She has published over 200 papers and received seven best paper or runner up awards. Her research has been supported by both governments (NSF, NIH, IARPA, AFOSR) and industry/foundations (Mistubishi, Cisco, AT&T, Google, IBM). More details are at http://www. cs.emory.edu/~lxiong.