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A Privacy Preserving Hybrid Neural-Crypto Computing-Based Image Steganography for Medical Images
Jambhale T.,
Published in Springer Science and Business Media Deutschland GmbH
2021
Volume: 57
   
Pages: 277 - 290
Abstract
With advancements in X-ray technology, there is an increase in the number of digital images used in the diagnosis of a patient. Whether it be a simple X-ray, MRI, CT scan or even a photo taken from a camera, the rise in the use of digital images has increased sharply. Though this has eased the entire process, it has brought the threat of cyber-attacks and breaches. The proposed method bridges this existing gap by incorporating suitable security mechanisms to preserve the privacy and confidentiality of medical diagnostic information of an individual. The approach utilizes neural networks to perform image steganography and combines it with a cryptographic algorithm (RSA) to secure medical images. The proposed method uses a two-level security providing a lower loss of 0.002188 on medical images improving upon existing image steganography techniques. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About the journal
JournalData powered by TypesetLecture Notes on Data Engineering and Communications Technologies
PublisherData powered by TypesetSpringer Science and Business Media Deutschland GmbH
ISSN23674512
Open AccessNo