Journal Article10.1007/s42979-023-02297-9
Efficient Neuroimaging Data Security and Encryption Using Pixel-Based Homomorphic Residue Number System
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TL;DR: The analysis demonstrates that the proposed RNS scheme is a fully homomorphic encryption (FHE) scheme that can encrypt and decrypt neuroimages without compromising any essential neural biomarker features and is robust against statistical attacks like histogram, brute force, correlation coefficient, and key sensitivity.
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About: This article is published in SN computer science. The article was published on 31 Oct 2023.
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Citations
Restoring private autism dataset from sanitized database using an optimized key produced from enhanced combined PSO-GWO framework
Md. Mokhlesur Rahman,Ravie Chandren Muniyandi,Shahnorbanun Sahran,Opeyemi Lateef Usman,Md. Moniruzzaman +4 more
TL;DR: This study enhanced the restoration process for ASD data's security and privacy by utilizing an optimal key produced via the Enhanced Combined PSO-GWO framework, which outperforms other existing methods on the 30-month autism children dataset.
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References
Deep Learning in Medical Image Analysis
TL;DR: This review covers computer-assisted analysis of images in the field of medical imaging and introduces the fundamentals of deep learning methods and their successes in image registration, detection of anatomical and cellular structures, tissue segmentation, computer-aided disease diagnosis and prognosis, and so on.
An overview of deep learning in medical imaging focusing on MRI
Alexander Lundervold,Alexander Lundervold,Arvid Lundervold,Arvid Lundervold,Arvid Lundervold +4 more
TL;DR: In this article, the authors provide a short overview of recent advances and some associated challenges in machine learning applied to medical image processing and image analysis, and provide a starting point for people interested in experimenting and perhaps contributing to the field of machine learning for medical imaging.
Implementing Gentry's fully-homomorphic encryption scheme
Craig Gentry,Shai Halevi +1 more
- 15 May 2011
TL;DR: In this article, the authors describe a working implementation of a variant of Gentry's fully homomorphic encryption scheme (STOC 2009), similar to the variant used in an earlier implementation effort by Smart and Vercauteren (PKC 2010).
Computing arbitrary functions of encrypted data
TL;DR: It is shown that this separation is possible: a "fully homomorphic" encryption scheme is described that keeps data private, but that allows a worker that does not have the secret decryption key to compute any (still encrypted) result of the data, even when the function of theData is very complex.
Improved Security for a Ring-Based Fully Homomorphic Encryption Scheme
TL;DR: In 2012, Lopez-Alt, Tromer and Vaikuntanathan proposed a fully homomorphic encryption scheme based on the Stehle and Steinfeld scheme as mentioned in this paper.