collaborators

16 papers

cs.CR2026

FakeI2V-Bench: Benchmarking the Applicability of Image-level Deepfake Detectors for Deepfake Video Detection

Pei Li, Sihan Chen, Delong Ran +1

Recent advances in video generation models have significantly intensified the deepfake threat, yet the current deepfake video detection benchmarks remain underdeveloped. In particu…

cs.CR2026

Robust Watermarks Meet Backdoored Models: Evading Diffusion Semantic Watermarks via Stealthy Backdoor

Jinyuan Liu, Tianshuo Cong, Pei Li +4

Although semantic watermarking is considered a promising safeguard for images generated by Latent Diffusion Models (LDMs), the reliance of the watermark detection pipeline on neura…

cs.CR2026

Cryptanalysis of LDPC-Based Pseudorandom Error-Correcting Codes

Tianrui Wang, Anyu Wang, Tianshuo Cong +3

Pseudorandom error-correcting codes (PRCs), a novel cryptographic primitive recently proposed at CRYPTO 2024, are primarily applied in undetectable watermarking schemes for large g…

cs.CR2026

Auditing Data Membership in Reinforcement Learning With Verifiable Rewards

Yule Liu, Heyi Zhang, Jinyi Zheng +6

Reinforcement Learning with Verifiable Rewards (RLVR) has become a core training stage in recent large language models (LLMs). Its reliance on non-public, high-value prompt sets ra…

cs.CR2026

Robustness Over Time: Understanding Adversarial Examples' Effectiveness on Longitudinal Versions of Large Language Models

Yugeng Liu, Tianshuo Cong, Zhengyu Zhao +3

Large Language Models (LLMs) undergo continuous updates to improve user experience. However, prior research on the security and safety implications of LLMs has primarily focused on…

cs.CR2026

From Defender to Devil? Unintended Risk Interactions Induced by LLM Defenses

Xiangtao Meng, Tianshuo Cong, Li Wang +4

Large Language Models (LLMs) have shown remarkable performance across various applications, but their deployment in real-world settings faces several risks, including jailbreak att…