Secure tumor classification by shallow neural network using homomorphic encryption

Secure tumor classification by shallow neural network using homomorphic encryption

Abstract Background Disclosure of patients’ genetic information in the process of applying machine learning techniques for tumor classification hinders the privacy of personal information. Homomorphic Encryption (HE), which supports operations between encrypted data, can be used as one of the tools...

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Bibliographic Details
Main Authors: Seungwan Hong, Jai Hyun Park, Wonhee Cho, Hyeongmin Choe, Jung Hee Cheon
Format: Article
Language:English
Published: BMC 2022-04-01
Series:BMC Genomics
Subjects:
Homomorphic encryption
Multi-label classification
Privacy
Neural network
Softmax activation
Online Access:https://doi.org/10.1186/s12864-022-08469-w

Internet

https://doi.org/10.1186/s12864-022-08469-w

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