Lock-LLM Workshop: Prevent Unauthorized Knowledge Use from Large Language Models - Deep Dive into Un-Distillate, Un-Finetunable, Un-Compressible, Un-Editable, and Un-Usable

Large Language Models (LLMs) have emerged as transformative tools across research and industry, revolutionizing how we interact with information. However, their immense capabilities bring critical security challenges—the same features that drive innovation can be exploited for malicious purposes through unauthorized distillation, fine-tuning, compression, or editing. These vulnerabilities pose severe threats, including intellectual property theft, the generation of sophisticated disinformation, the bypass of safety alignments, and the erosion of user trust in AI systems.

This workshop aims to bring together researchers and practitioners from academia and industry who are advancing the frontiers of LLM security and protection. We seek to confront the unauthorized use of LLMs head-on by exploring novel and robust mechanisms designed to make these models inherently resistant to exploitation while maintaining their beneficial capabilities. The workshop also hosts the 2025 TrustAI Rising Star Award.

Topics of interest include, but are not limited to:
1. Un-Distillable LLMs: Preventing unauthorized model replication and intellectual property theft
2. Un-Finetunable LLMs: Resisting malicious parameter updates and behavior alterations
3. Un-Compressible LLMs: Maintaining model integrity against unauthorized compression
4. Un-Editable LLMs: Safeguarding against knowledge tampering and misinformation injection
5. Un-Usable LLMs: Ensuring traceability and preventing misuse through watermarking and verification