This paper presents AutoMarks, an automated and transferable watermarking framework that leverages graph neural networks to reduce the watermark search overheads during the placement stage. AutoMarks's novel automated watermark search is accomplished by (i) constructing novel graph and node features with physical, semantic, and design constraint-aware representation; (ii) designing a data-efficient sampling strategy for watermarking fidelity label collection; and (iii) leveraging a graph neural network to learn the connectivity between cells and predict the watermarking fidelity on unseen layouts. Extensive evaluations on ISPD'15 and ISPD'19 benchmarks demonstrate that our proposed automated methodology: (i) is capable of finding quality-preserving watermarks in a short time; and (ii) is transferable across various designs, i.e., AutoMarks trained on one layout is generalizable to other benchmark circuits. AutoMarks is also resilient against potential watermark removal and forging attacks
SKeDA: A Generative Watermarking Framework for Text-to-video Diffusion Models
School of Electronic and Information Engineering, Anhui University（安徽大学电子与信息工程学院）；Anhui Province Key Laboratory of Digital Security and the CAS Key Laboratory of Electromagnetic Space Information, University of Science and Technology of China（安徽省数字安全重点实验室和中国科学院电磁空间信息重点实验室，中国科学技术大学）；School of Computing, National University of Singapore（新加坡国立大学计算机学院）
RMCW: A Deletion-Robust Watermark Based on Reed--Muller Codes for Language Models
Tsinghua University（清华大学）；University of Wisconsin–Madison（威斯康星大学麦迪逊分校）；Shanghai Qi Zhi Institute（上海期智研究院）；The Chinese University of Hong Kong, Shenzhen（香港中文大学（深圳））；Chinese Academy of Sciences（中国科学院）；Xiongan AI Institute（雄安人工智能研究院）
Fragile Model Watermark for integrity protection: leveraging boundary volatility and sensitive sample-pairing
East China Normal University（华东师范大学）；Guangxi Normal University（广西师范大学）；Shenzhen Research Institute of Big Data, The Chinese University of Hong Kong（香港中文大学深圳大数据研究院）
STAF: Leveraging LLMs for Automated Attack Tree-Based Security Test Generation
Department of Systems Design Engineering, University of Waterloo, ON Canada（滑铁卢大学系统设计工程系）；Smart Calibration and Virtual Testing Department, AVL List GmbH, Graz, Austria（AVL List GmbH智能校准与虚拟测试部门）；Department of Computer Science, Western University, London, ON, Canada（温哥华大学计算机科学系）
