Privacy Preserving Classification of EEG Data Using Machine Learning and Homomorphic Encryption

Privacy Preserving Classification of EEG Data Using Machine Learning and Homomorphic Encryption

Data privacy is a major concern when accessing and processing sensitive medical data. A promising approach among privacy-preserving techniques is homomorphic encryption (HE), which allows for computations to be performed on encrypted data. Currently, HE still faces practical limitations related to h...

Full description

Bibliographic Details
Main Authors: Andreea Bianca Popescu, Ioana Antonia Taca, Cosmin Ioan Nita, Anamaria Vizitiu, Robert Demeter, Constantin Suciu, Lucian Mihai Itu
Format: Article
Language:English
Published: MDPI AG 2021-08-01
Series:Applied Sciences
Subjects:
privacy-preserving computations
homomorphic encryption
machine learning
EEG signals
Online Access:https://www.mdpi.com/2076-3417/11/16/7360

Internet

https://www.mdpi.com/2076-3417/11/16/7360

Similar Items