3 citations · 10 across the 17 of their papers we have counts for
17 papers
ALIEN: Analytic Latent Watermarking for Controllable Generation
Liangqi Lei, Keke Gai, Jing Yu +1
Watermarking is a technical alternative to safeguarding intellectual property and reducing misuse. Existing methods focus on optimizing watermarked latent variables to balance wate…
Trajectory-Aware Information Matching for Multi-Step Gradient Inversion in Federated Learning
Li Xia, Jing Yu, Zheng Liu +3
Federated learning enables distributed information sharing and collaborative model training without exposing raw client data. However, shared gradients or model updates may still c…
A Vision-Language Pre-training Model-Guided Approach for Mitigating Backdoor Attacks in Federated Learning
Keke Gai, Dongjue Wang, Jing Yu +2
Defending backdoor attacks in Federated Learning (FL) under heterogeneous client data distributions encounters limitations balancing effectiveness and privacy-preserving, while mos…
LLAMA: Multi-Feedback Smart Contract Fuzzing Framework with LLM-Guided Seed Generation
Keke Gai, Haochen Liang, Jing Yu +2
Smart contracts play a pivotal role in blockchain ecosystems, and fuzzing remains an important approach to securing smart contracts. Even though mutation scheduling is a key factor…
AGATE: Stealthy Black-box Watermarking for Multimodal Model Copyright Protection
Jianbo Gao, Keke Gai, Jing Yu +2
Recent advancement in large-scale Artificial Intelligence (AI) models offering multimodal services have become foundational in AI systems, making them prime targets for model theft…
PCDiff: Proactive Control for Ownership Protection in Diffusion Models with Watermark Compatibility
Keke Gai, Ziyue Shen, Jing Yu +2
With the growing demand for protecting the intellectual property (IP) of text-to-image diffusion models, we propose PCDiff -- a proactive access control framework that redefines mo…
Secure and Efficient Watermarking for Latent Diffusion Models in Model Distribution Scenarios
Liangqi Lei, Keke Gai, Jing Yu +2
Latent diffusion models have exhibited considerable potential in generative tasks. Watermarking is considered to be an alternative to safeguard the copyright of generative models a…
Vertical Federated Continual Learning via Evolving Prototype Knowledge
Shuo Wang, Keke Gai, Jing Yu +2
Vertical Federated Learning (VFL) has garnered significant attention as a privacy-preserving machine learning framework for sample-aligned feature federation. However, traditional…
Adaptive Prototype Knowledge Transfer for Federated Learning with Mixed Modalities and Heterogeneous Tasks
Keke Gai, Mohan Wang, Jing Yu +2
Multimodal Federated Learning (MFL) with mixed modalities enables unimodal and multimodal clients to collaboratively train models while ensuring clients' privacy. As a representati…
SLVC-DIDA: Signature-less Verifiable Credential-based Issuer-hiding and Multi-party Authentication for Decentralized Identity
Tianxiu Xie, Keke Gai, Jing Yu +2
As an emerging paradigm in digital identity, Decentralized Identity (DID) appears advantages over traditional identity management methods in a variety of aspects, e.g., enhancing u…
Watermarking Visual Concepts for Diffusion Models
Liangqi Lei, Keke Gai, Jing Yu +2
The personalization techniques of diffusion models succeed in generating images with specific concepts. This ability also poses great threats to copyright protection and network se…
IIU: Independent Inference Units for Knowledge-based Visual Question Answering
Yili Li, Jing Yu, Keke Gai +1
Knowledge-based visual question answering requires external knowledge beyond visible content to answer the question correctly. One limitation of existing methods is that they focus…
A2-DIDM: Privacy-preserving Accumulator-enabled Auditing for Distributed Identity of DNN Model
Tianxiu Xie, Keke Gai, Jing Yu +1
Recent booming development of Generative Artificial Intelligence (GenAI) has facilitated model commercialization to reinforce the model performance, including licensing or trading…
DiffuseTrace: A Transparent and Flexible Watermarking Scheme for Latent Diffusion Model
Liangqi Lei, Keke Gai, Jing Yu +1
Latent Diffusion Models (LDMs) enable a wide range of applications but raise ethical concerns regarding illegal utilization. Adding watermarks to generative model outputs is a vita…
Binary Linear Tree Commitment-based Ownership Protection for Distributed Machine Learning
Tianxiu Xie, Keke Gai, Jing Yu +1
Distributed machine learning enables parallel training of extensive datasets by delegating computing tasks across multiple workers. Despite the cost reduction benefits of distribut…
Watermarking Vision-Language Pre-trained Models for Multi-modal Embedding as a Service
Yuanmin Tang, Jing Yu, Keke Gai +4
Recent advances in vision-language pre-trained models (VLPs) have significantly increased visual understanding and cross-modal analysis capabilities. Companies have emerged to prov…
EASTER: Embedding Aggregation-based Heterogeneous Models Training in Vertical Federated Learning
Shuo Wang, Keke Gai, Jing Yu +3
Vertical federated learning has garnered significant attention as it allows clients to train machine learning models collaboratively without sharing local data, which protects the…