May 30, 2019 · In the framework, the cloud server can first generate a model using outsourced machine learning algorithms and then process testing data from ...
In this article, we propose a framework that enables a secure intelligent network with the assistance of cloud-as- sisted privacy-preserving machine learning.
Oct 22, 2024 · ... Yu et al. [15] propose a system that utilizes cloud-assisted privacy-preserving machine learning, emphasizing differential privacy and ...
May 30, 2019 · This article proposes a framework that enables a secure intelligent network with the assistance of cloud-assisted privacy-preserving machine ...
It is shown that it is feasible and practical to train neural networks using encrypted data and to make encrypted predictions, and also return the ...
People also ask
What are the privacy preserving techniques in machine learning?
What is the primary concern addressed by privacy preserving machine learning techniques?
What is homomorphic encryption applied to the cloud computing security?
What is privacy in machine learning?
Machine Learning-assisted cloud computing model (ML-CCM) with big data analytics has been proposed to increase security and improve data transmission.
range from an intelligent edge computing framework that combines AI and IoT to enabling secure intelligent networks with cloud-assisted privacy-preserving ML.
Jan 25, 2024 · This paper proposes a novel privacy-preserving mechanism that uses a combination of homomorphic encryption, differential privacy, and secure multi-party ...
2016) introduces a cloud-based frame- work that enables secure management and analysis of large, and potentially sensitive, datasets. It claims to ensure secure.
Data analytics has been widely used to extract insights from massive amount of data via machine learning techniques, such as deep neutral networks, decision ...