activity
20232026
most citedPrivacy Leakage on DNNs: A Survey of Model Inversion Attacks and Defenses

7 citations · 9 across the 8 of their papers we have counts for

collaborators

9 papers

cs.CL2026

CHILLGuard: Towards Fine-Grained Chinese LLM Safety Guardrail with Scalable Data Construction and Model-aware Preference Alignment

Wenbo Yu, Bohua Wang, Hao Fang +10

Malicious content generated from large language models (LLMs) could pose severe safety risks and ethical concerns. While existing LLM safety guardrails excel in English or multilin…

cs.CR2026

Bypassing Copyright Protection in Diffusion-based Customization via Two-Stage Latent Feature Optimization

Ziang Xu, Wenbo Yu, Hongyao Yu +6

With the growing concerns over copyright infringement in diffusion-based customization, adversarial attacks have emerged as a prominent defense strategy to prevent malicious conten…

cs.CV2026

Enhancing Gradient Inversion Attacks in Federated Learning via Hierarchical Feature Optimization

Hao Fang, Wenbo Yu, Bin Chen +4

Federated Learning (FL) has emerged as a compelling paradigm for privacy-preserving distributed machine learning, allowing multiple clients to collaboratively train a global model…

cs.IT2024

Editable-DeepSC: Reliable Cross-Modal Semantic Communications for Facial Editing

Bin Chen, Wenbo Yu, Qinshan Zhang +4

Interactive computer vision (CV) plays a crucial role in various real-world applications, whose performance is highly dependent on communication networks. Nonetheless, the data-ori…

cs.CV2024★ 2 cited

MIBench: A Comprehensive Framework for Benchmarking Model Inversion Attack and Defense

Yixiang Qiu, Hongyao Yu, Hao Fang +6

Model Inversion (MI) attacks aim at leveraging the output information of target models to reconstruct privacy-sensitive training data, raising critical concerns regarding the priva…

cs.CV2024

One Perturbation is Enough: On Generating Universal Adversarial Perturbations against Vision-Language Pre-training Models

Hao Fang, Jiawei Kong, Wenbo Yu +5

Vision-Language Pre-training (VLP) models have exhibited unprecedented capability in many applications by taking full advantage of the multimodal alignment. However, previous studi…

cs.AI2024

GI-NAS: Boosting Gradient Inversion Attacks Through Adaptive Neural Architecture Search

Wenbo Yu, Hao Fang, Bin Chen +5

Gradient Inversion Attacks invert the transmitted gradients in Federated Learning (FL) systems to reconstruct the sensitive data of local clients and have raised considerable priva…

cs.CV2024★ 7 cited

Privacy Leakage on DNNs: A Survey of Model Inversion Attacks and Defenses

Hao Fang, Yixiang Qiu, Hongyao Yu +7

Deep Neural Networks (DNNs) have revolutionized various domains with their exceptional performance across numerous applications. However, Model Inversion (MI) attacks, which disclo…

cs.IT2023

Editable-DeepSC: Cross-Modal Editable Semantic Communication Systems

Wenbo Yu, Bin Chen, Qinshan Zhang +1

Different from data-oriented communication systems that primarily focus on how to accurately transmit every bit of data, task-oriented semantic communication systems only transmit…