An Efficient Outsourced Privacy Preserving Machine Learning Scheme With Public Verifiability

An Efficient Outsourced Privacy Preserving Machine Learning Scheme With Public Verifiability

Cloud computing has been widely applied in numerous applications for storage and data analytics tasks. However, cloud servers engaged through a third party cannot be fully trusted by multiple data users. Thus, security and privacy concerns become the main obstructions to use machine learning service...

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Bibliographic Details
Main Authors: Alzubair Hassan, Rafik Hamza, Hongyang Yan, Ping Li
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Cloud computing
machine learning
public verifiability
proxy re-encryption
differential privacy
Online Access:https://ieeexplore.ieee.org/document/8862813/

Internet

https://ieeexplore.ieee.org/document/8862813/

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