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When machine learning meets privacy in 6G: A survey
The rapid-develo** Artificial Intelligence (AI) technology, fast-growing network traffic, and
emerging intelligent applications (eg, autonomous driving, virtual reality, etc.) urgently …
emerging intelligent applications (eg, autonomous driving, virtual reality, etc.) urgently …
Securing machine learning in the cloud: A systematic review of cloud machine learning security
With the advances in machine learning (ML) and deep learning (DL) techniques, and the
potency of cloud computing in offering services efficiently and cost-effectively, Machine …
potency of cloud computing in offering services efficiently and cost-effectively, Machine …
POSEIDON: Privacy-preserving federated neural network learning
In this paper, we address the problem of privacy-preserving training and evaluation of neural
networks in an $ N $-party, federated learning setting. We propose a novel system …
networks in an $ N $-party, federated learning setting. We propose a novel system …
When homomorphic encryption marries secret sharing: Secure large-scale sparse logistic regression and applications in risk control
Logistic Regression (LR) is the most widely used machine learning model in industry for its
efficiency, robustness, and interpretability. Due to the problem of data isolation and the …
efficiency, robustness, and interpretability. Due to the problem of data isolation and the …
Scalable privacy-preserving distributed learning
In this paper, we address the problem of privacy-preserving distributed learning and the
evaluation of machine-learning models by analyzing it in the widespread MapReduce …
evaluation of machine-learning models by analyzing it in the widespread MapReduce …
SecureNLP: A system for multi-party privacy-preserving natural language processing
Natural language processing (NLP) allows a computer program to understand human
language as it is spoken, and has been increasingly deployed in a growing number of …
language as it is spoken, and has been increasingly deployed in a growing number of …
A multicenter random forest model for effective prognosis prediction in collaborative clinical research network
Background The accuracy of a prognostic prediction model has become an essential aspect
of the quality and reliability of the health-related decisions made by clinicians in modern …
of the quality and reliability of the health-related decisions made by clinicians in modern …
A comprehensive survey on secure outsourced computation and its applications
With the ever-increasing requirement of storage and computation resources, it is unrealistic
for local devices (with limited sources) to implement large-scale data processing. Therefore …
for local devices (with limited sources) to implement large-scale data processing. Therefore …
HE-friendly algorithm for privacy-preserving SVM training
Support vector machine (SVM) is one of the most popular machine learning algorithms. It
predicts a pre-defined output variable in real-world applications. Machine learning on …
predicts a pre-defined output variable in real-world applications. Machine learning on …
[HTML][HTML] Multi-fault detection and classification of wind turbines using stacking classifier
Wind turbines are widely used worldwide to generate clean, renewable energy. The biggest
issue with a wind turbine is reducing failures and downtime, which lowers costs associated …
issue with a wind turbine is reducing failures and downtime, which lowers costs associated …