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Chaos blended cellular automata on fractals: the effective way of reconfigurable hardware assisted medical image privacy

In more recent times data continues to be generated at a very unprecedented scale. This is a result of the pervasive nature of modern-day digitisation. As such, it is absolutely critical that this data only be accessed by the trusted parties concerned in an effort to maintain the privacy of individu...

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Autores principales: Sivaraman, R., Vijaykumar, Ajay, Savarinathan, Prem, Jayapalan, Avila
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9014785/
https://www.ncbi.nlm.nih.gov/pubmed/35463222
http://dx.doi.org/10.1007/s11042-022-13165-8
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author Sivaraman, R.
Vijaykumar, Ajay
Savarinathan, Prem
Jayapalan, Avila
author_facet Sivaraman, R.
Vijaykumar, Ajay
Savarinathan, Prem
Jayapalan, Avila
author_sort Sivaraman, R.
collection PubMed
description In more recent times data continues to be generated at a very unprecedented scale. This is a result of the pervasive nature of modern-day digitisation. As such, it is absolutely critical that this data only be accessed by the trusted parties concerned in an effort to maintain the privacy of individuals. One particular type data that could severely compromise the identity and privacy of an individual is ‘medical data’. With a focus on medical images, this work proposes a novel ‘fractalized’ chaos-cellular automata encryption scheme, implemented on Cyclone IV EP2C35F672C6 FPGA, resulting in a hardware-based concurrent security solution. The scheme entails three stages of diffusion, which arise from different mechanisms. In tandem with the diffusion process is the “On the Fly” process of confusion governed by a Linear feedback Shift Register (LFSR), all of which in implemented by applying the nature of fractals. The security architecture occupies 16,351 Logic Elements (LEs) with 230 registers on the target FPGA with the power dissipation of 133.39 mW. Further, the encryption achieves near zero correlation with the average entropy of 15.17156 that ensures the statistical properties. In addition, the security framework requires 12.13 ms to encrypt a 256 × 256 × 16 DICOM image which results in the throughput of 86.44 Mbps. The proposed encryption resists the brute force attack and chosen plain text attack by achieving a very large span of keyspace.
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spelling pubmed-90147852022-04-19 Chaos blended cellular automata on fractals: the effective way of reconfigurable hardware assisted medical image privacy Sivaraman, R. Vijaykumar, Ajay Savarinathan, Prem Jayapalan, Avila Multimed Tools Appl Article In more recent times data continues to be generated at a very unprecedented scale. This is a result of the pervasive nature of modern-day digitisation. As such, it is absolutely critical that this data only be accessed by the trusted parties concerned in an effort to maintain the privacy of individuals. One particular type data that could severely compromise the identity and privacy of an individual is ‘medical data’. With a focus on medical images, this work proposes a novel ‘fractalized’ chaos-cellular automata encryption scheme, implemented on Cyclone IV EP2C35F672C6 FPGA, resulting in a hardware-based concurrent security solution. The scheme entails three stages of diffusion, which arise from different mechanisms. In tandem with the diffusion process is the “On the Fly” process of confusion governed by a Linear feedback Shift Register (LFSR), all of which in implemented by applying the nature of fractals. The security architecture occupies 16,351 Logic Elements (LEs) with 230 registers on the target FPGA with the power dissipation of 133.39 mW. Further, the encryption achieves near zero correlation with the average entropy of 15.17156 that ensures the statistical properties. In addition, the security framework requires 12.13 ms to encrypt a 256 × 256 × 16 DICOM image which results in the throughput of 86.44 Mbps. The proposed encryption resists the brute force attack and chosen plain text attack by achieving a very large span of keyspace. Springer US 2022-04-18 2022 /pmc/articles/PMC9014785/ /pubmed/35463222 http://dx.doi.org/10.1007/s11042-022-13165-8 Text en © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Article
Sivaraman, R.
Vijaykumar, Ajay
Savarinathan, Prem
Jayapalan, Avila
Chaos blended cellular automata on fractals: the effective way of reconfigurable hardware assisted medical image privacy
title Chaos blended cellular automata on fractals: the effective way of reconfigurable hardware assisted medical image privacy
title_full Chaos blended cellular automata on fractals: the effective way of reconfigurable hardware assisted medical image privacy
title_fullStr Chaos blended cellular automata on fractals: the effective way of reconfigurable hardware assisted medical image privacy
title_full_unstemmed Chaos blended cellular automata on fractals: the effective way of reconfigurable hardware assisted medical image privacy
title_short Chaos blended cellular automata on fractals: the effective way of reconfigurable hardware assisted medical image privacy
title_sort chaos blended cellular automata on fractals: the effective way of reconfigurable hardware assisted medical image privacy
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9014785/
https://www.ncbi.nlm.nih.gov/pubmed/35463222
http://dx.doi.org/10.1007/s11042-022-13165-8
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