collaborators

9 papers

cs.CR2026

Tracing Provenance and Detecting Tampering with Complementary LLM Watermarks

Xiaoyan Feng, Yanjun Zhang, He Zhang +2

Watermarking LLM-generated text is an important task for tracing its provenance. Existing LLM watermarks preserve provenance under editing, but this same robustness allows an adver…

cs.LG2026

ARES: Scalable and Practical Gradient Inversion Attack in Federated Learning through Activation Recovery

Zirui Gong, Leo Yu Zhang, Yanjun Zhang +4

Federated Learning (FL) enables collaborative model training by sharing model updates instead of raw data, aiming to protect user privacy. However, recent studies reveal that these…

cs.CR2026

Towards Model Extraction Attacks in GAN-Based Image Translation via Domain Shift Mitigation

Di Mi, Yanjun Zhang, Leo Yu Zhang +4

Model extraction attacks (MEAs) enable an attacker to replicate the functionality of a victim deep neural network (DNN) model by only querying its API service remotely, posing a se…

cs.CR2026

Less Is More -- Until It Breaks: Security Pitfalls of Vision Token Compression in Large Vision-Language Models

Xiaomei Zhang, Zhaoxi Zhang, Leo Yu Zhang +3

Visual token compression is widely adopted to improve the inference efficiency of Large Vision-Language Models (LVLMs), enabling their deployment in latency-sensitive and resource-…

cs.LG2025

TED++: Submanifold-Aware Backdoor Detection via Layerwise Tubular-Neighbourhood Screening

Nam Le, Leo Yu Zhang, Kewen Liao +2

As deep neural networks power increasingly critical applications, stealthy backdoor attacks, where poisoned training inputs trigger malicious model behaviour while appearing benign…

cs.CR2025

Character-Level Perturbations Disrupt LLM Watermarks

Zhaoxi Zhang, Xiaomei Zhang, Yanjun Zhang +5

Large Language Model (LLM) watermarking embeds detectable signals into generated text for copyright protection, misuse prevention, and content detection. While prior studies evalua…