4 papers
Anomaly Detection and Generation with Diffusion Models: A Survey
Yang Liu, Jing Liu, Chengfang Li +7
Anomaly detection (AD) plays a pivotal role across diverse domains, including cybersecurity, finance, healthcare, and industrial manufacturing, by identifying unexpected patterns t…
A proof of contribution in blockchain using game theoretical deep learning model
Jin Wang
Building elastic and scalable edge resources is an inevitable prerequisite for providing platform-based smart city services. Smart city services are delivered through edge computin…
MGIC: A Multi-Label Gradient Inversion Attack based on Canny Edge Detection on Federated Learning
Can Liu, Jin Wang
As a new distributed computing framework that can protect data privacy, federated learning (FL) has attracted more and more attention in recent years. It receives gradients from us…
AFGI: Towards Accurate and Fast-convergent Gradient Inversion Attack in Federated Learning
Can Liu, Jin Wang, and Yipeng Zhou +3
Federated learning (FL) empowers privacypreservation in model training by only exposing users' model gradients. Yet, FL users are susceptible to gradient inversion attacks (GIAs) w…