most citedDecentralized Multimedia Data Sharing in IoV: A Learning-based Equilibrium of Supply and Demand

10 citations · 34 across the 17 of their papers we have counts for

collaborators

17 papers

cs.CR2024

PSA: Private Set Alignment for Secure and Collaborative Analytics on Large-Scale Data

Jiabo Wang, Elmo Xuyun Huang, Pu Duan +2

Enforcement of privacy regulation is essential for collaborative data analytics. In this work, we address a scenario in which two companies expect to securely join their datasets w…

cs.CR20241 cited

Towards Physical World Backdoor Attacks against Skeleton Action Recognition

Qichen Zheng, Yi Yu, Siyuan Yang +3

Skeleton Action Recognition (SAR) has attracted significant interest for its efficient representation of the human skeletal structure. Despite its advancements, recent studies have…

cs.CR2024

Unlearnable Examples Detection via Iterative Filtering

Yi Yu, Qichen Zheng, Siyuan Yang +6

Deep neural networks are proven to be vulnerable to data poisoning attacks. Recently, a specific type of data poisoning attack known as availability attacks has led to the failure…

cs.CR20241 cited

Privacy-Preserving Federated Unlearning with Certified Client Removal

Ziyao Liu, Huanyi Ye, Yu Jiang +4

In recent years, Federated Unlearning (FU) has gained attention for addressing the removal of a client's influence from the global model in Federated Learning (FL) systems, thereby…

cs.CV2024

Object-level Copy-Move Forgery Image Detection based on Inconsistency Mining

Jingyu Wang, Niantai Jing, Ziyao Liu +4

In copy-move tampering operations, perpetrators often employ techniques, such as blurring, to conceal tampering traces, posing significant challenges to the detection of object-lev…

cs.CR202410 cited

Decentralized Multimedia Data Sharing in IoV: A Learning-based Equilibrium of Supply and Demand

Jiani Fan, Minrui Xu, Jiale Guo +4

The Internet of Vehicles (IoV) has great potential to transform transportation systems by enhancing road safety, reducing traffic congestion, and improving user experience through…