Efficiency optimization techniques in privacy-preserving federated learning with homomorphic encryption: A brief survey

Q Xie, S Jiang, L Jiang, Y Huang, Z Zhao… - IEEE Internet of …, 2024 - ieeexplore.ieee.org
Federated learning (FL) offers distributed machine learning on edge devices. However, the
FL model raises privacy concerns. Various techniques, such as homomorphic encryption …

A survey on vertical federated learning: From a layered perspective

L Yang, D Chai, J Zhang, Y Jin, L Wang, H Liu… - arXiv preprint arXiv …, 2023 - arxiv.org
Vertical federated learning (VFL) is a promising category of federated learning for the
scenario where data is vertically partitioned and distributed among parties. VFL enriches the …

Path signature-based xai-enabled network time series classification

L Sun, Y Wang, Y Ren, F Xia - Science China Information Sciences, 2024 - Springer
Classifying network time series (NTS) is crucial for automating network administration and
ensuring cyberspace security. It enables the detection of anomalies, the identification of …

SGBoost: An efficient and privacy-preserving vertical federated tree boosting framework

J Zhao, H Zhu, W Xu, F Wang, R Lu… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Aiming at balancing data privacy and availability, Google introduces the concept of
federated learning, which can construct global machine learning models over multiple …

VFLR: An efficient and privacy-preserving vertical federated framework for logistic regression

J Zhao, H Zhu, F Wang, R Lu, E Wang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
With the explosive growth of data volume and computing capability, federated learning,
which involves constructing global models over multiple data islands, has demonstrated its …

IIFS: An improved incremental feature selection method for protein sequence processing

C Meng, Y Yuan, H Zhao, Y Pei, Z Li - Computers in Biology and Medicine, 2023 - Elsevier
Motivation Discrete features can be obtained from protein sequences using a feature
extraction method. These features are the basis of downstream processing of protein data …

A multi-source transfer-based decision-making method with domain consistency and contributions

X Jia, W Chang, C Fu - Computers & Industrial Engineering, 2024 - Elsevier
Large volumes of historical data that characterize the preferences of decision-makers are
generated and recorded. Each decision-maker's historical data contain different knowledge …

Achieving federated logistic regression training towards model confidentiality with semi-honest TEE

F Wang, H Zhu, X Liu, Y Zheng, H Li, J Hua - Information Sciences, 2024 - Elsevier
In the distributed machine learning field, federated learning (FL) serves as a highly effective
framework for dismantling data silos and integrating data from multiple sources. However …

Cross-domain recommender system with embedding-and mapping-based knowledge correlation

C Jin, Y Duan, L Zhou, F Li - Knowledge-Based Systems, 2024 - Elsevier
A knowledge transfer-based cross-domain recommender system is currently a research
hotspot. Existing research has reached a high level of maturity in mining potential …

ELXGB: An Efficient and Privacy-Preserving XGBoost for Vertical Federated Learning

W Xu, H Zhu, Y Zheng, F Wang, J Zhao… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
With the rapid growth of Internet data volumes, big data analysis technologies have
gradually permeated all aspects of life. However, the existence of data silos and the …