activity
20182025
most citedResearch on the Security of Blockchain Data: A Survey

28 citations · 48 across the 23 of their papers we have counts for

collaborators

23 papers

cs.LG2025

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…

cs.SE2025

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…

cs.CR2025

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…

cs.CR2025

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…

cs.CV2025

Missing Target-Relevant Information Prediction with World Model for Accurate Zero-Shot Composed Image Retrieval

Yuanmin Tang, Jing Yu, Keke Gai +4

Zero-Shot Composed Image Retrieval (ZS-CIR) involves diverse tasks with a broad range of visual content manipulation intent across domain, scene, object, and attribute. The key cha…

cs.CR2025★ 1 cited

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…

cs.LG2025

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…

cs.LG2025★ 1 cited

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…

cs.CR2025★ 2 cited

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…

cs.CR2024

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…

cs.CV2024

Denoise-I2W: Mapping Images to Denoising Words for Accurate Zero-Shot Composed Image Retrieval

Yuanmin Tang, Jing Yu, Keke Gai +4

Zero-Shot Composed Image Retrieval (ZS-CIR) supports diverse tasks with a broad range of visual content manipulation intentions that can be related to domain, scene, object, and at…

cs.CV2024★ 6 cited

T2VIndexer: A Generative Video Indexer for Efficient Text-Video Retrieval

Yili Li, Jing Yu, Keke Gai +3

Current text-video retrieval methods mainly rely on cross-modal matching between queries and videos to calculate their similarity scores, which are then sorted to obtain retrieval…

cs.CV2024

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…

cs.CV2024

Visual-Semantic Decomposition and Partial Alignment for Document-based Zero-Shot Learning

Xiangyan Qu, Jing Yu, Keke Gai +5

Recent work shows that documents from encyclopedias serve as helpful auxiliary information for zero-shot learning. Existing methods align the entire semantics of a document with co…

cs.CR2024

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…

cs.CR2024★ 3 cited

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…

cs.LG2024

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…

cs.CR2023

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…

cs.LG2023★ 3 cited

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…

cs.CV2023★ 2 cited

Align before Search: Aligning Ads Image to Text for Accurate Cross-Modal Sponsored Search

Yuanmin Tang, Jing Yu, Keke Gai +4

Cross-Modal sponsored search displays multi-modal advertisements (ads) when consumers look for desired products by natural language queries in search engines. Since multi-modal ads…

cs.CV2023★ 2 cited

Context-I2W: Mapping Images to Context-dependent Words for Accurate Zero-Shot Composed Image Retrieval

Yuanmin Tang, Jing Yu, Keke Gai +4

Different from Composed Image Retrieval task that requires expensive labels for training task-specific models, Zero-Shot Composed Image Retrieval (ZS-CIR) involves diverse tasks wi…

cs.DC2021

Optimal Data Placement for Data-Sharing Scientific Workflows in Heterogeneous Edge-Cloud Computing Environments

Xin Du, Songtao Tang, Zhihui Lu +3

The heterogeneous edge-cloud computing paradigm can provide a more optimal direction to deploy scientific workflows than traditional distributed computing or cloud computing enviro…

cs.CR2018★ 28 cited

Research on the Security of Blockchain Data: A Survey

Liehuang Zhu, Baokun Zheng, Meng Shen +5

With the more and more extensive application of blockchain, blockchain security has been widely concerned by the society and deeply studied by scholars. Moreover, the security of b…