Search Results for author: Longfei Zheng

Found 7 papers, 0 papers with code

Privacy Inference-Empowered Stealthy Backdoor Attack on Federated Learning under Non-IID Scenarios

no code implementations13 Jun 2023 Haochen Mei, Gaolei Li, Jun Wu, Longfei Zheng

In this paper, we propose a novel privacy inference-empowered stealthy backdoor attack (PI-SBA) scheme for FL under non-IID scenarios.

Backdoor Attack Federated Learning

Towards Scalable and Privacy-Preserving Deep Neural Network via Algorithmic-Cryptographic Co-design

no code implementations17 Dec 2020 Jun Zhou, Longfei Zheng, Chaochao Chen, Yan Wang, Xiaolin Zheng, Bingzhe Wu, Cen Chen, Li Wang, Jianwei Yin

In this paper, we propose SPNN - a Scalable and Privacy-preserving deep Neural Network learning framework, from algorithmic-cryptographic co-perspective.

Privacy Preserving

ASFGNN: Automated Separated-Federated Graph Neural Network

no code implementations6 Nov 2020 Longfei Zheng, Jun Zhou, Chaochao Chen, Bingzhe Wu, Li Wang, Benyu Zhang

Specifically, to solve the data Non-IID problem, we first propose a separated-federated GNN learning model, which decouples the training of GNN into two parts: the message passing part that is done by clients separately, and the loss computing part that is learnt by clients federally.

Bayesian Optimization Graph Neural Network

Vertically Federated Graph Neural Network for Privacy-Preserving Node Classification

no code implementations25 May 2020 Chaochao Chen, Jun Zhou, Longfei Zheng, Huiwen Wu, Lingjuan Lyu, Jia Wu, Bingzhe Wu, Ziqi Liu, Li Wang, Xiaolin Zheng

Recently, Graph Neural Network (GNN) has achieved remarkable progresses in various real-world tasks on graph data, consisting of node features and the adjacent information between different nodes.

Classification General Classification +3

Industrial Scale Privacy Preserving Deep Neural Network

no code implementations11 Mar 2020 Longfei Zheng, Chaochao Chen, Yingting Liu, Bingzhe Wu, Xibin Wu, Li Wang, Lei Wang, Jun Zhou, Shuang Yang

Deep Neural Network (DNN) has been showing great potential in kinds of real-world applications such as fraud detection and distress prediction.

Fraud Detection Privacy Preserving

Privacy Preserving PCA for Multiparty Modeling

no code implementations6 Feb 2020 Yingting Liu, Chaochao Chen, Longfei Zheng, Li Wang, Jun Zhou, Guiquan Liu, Shuang Yang

In this paper, we present a general multiparty modeling paradigm with Privacy Preserving Principal Component Analysis (PPPCA) for horizontally partitioned data.

Fraud Detection Privacy Preserving

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