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Medical Image Encryption: An Application for Improved Padding Based GGH Encryption Algorithm

Medical images are regarded as important and sensitive data in the medical informatics systems. For transferring medical images over an insecure network, developing a secure encryption algorithm is necessary. Among the three main properties of security services (i.e., confidentiality, integrity, and...

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Autores principales: Sokouti, Massoud, Zakerolhosseini, Ali, Sokouti, Babak
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Bentham Open 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5090780/
https://www.ncbi.nlm.nih.gov/pubmed/27857824
http://dx.doi.org/10.2174/1874431101610010011
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author Sokouti, Massoud
Zakerolhosseini, Ali
Sokouti, Babak
author_facet Sokouti, Massoud
Zakerolhosseini, Ali
Sokouti, Babak
author_sort Sokouti, Massoud
collection PubMed
description Medical images are regarded as important and sensitive data in the medical informatics systems. For transferring medical images over an insecure network, developing a secure encryption algorithm is necessary. Among the three main properties of security services (i.e., confidentiality, integrity, and availability), the confidentiality is the most essential feature for exchanging medical images among physicians. The Goldreich Goldwasser Halevi (GGH) algorithm can be a good choice for encrypting medical images as both the algorithm and sensitive data are represented by numeric matrices. Additionally, the GGH algorithm does not increase the size of the image and hence, its complexity will remain as simple as O(n(2)). However, one of the disadvantages of using the GGH algorithm is the Chosen Cipher Text attack. In our strategy, this shortcoming of GGH algorithm has been taken in to consideration and has been improved by applying the padding (i.e., snail tour XORing), before the GGH encryption process. For evaluating their performances, three measurement criteria are considered including (i) Number of Pixels Change Rate (NPCR), (ii) Unified Average Changing Intensity (UACI), and (iii) Avalanche effect. The results on three different sizes of images showed that padding GGH approach has improved UACI, NPCR, and Avalanche by almost 100%, 35%, and 45%, respectively, in comparison to the standard GGH algorithm. Also, the outcomes will make the padding GGH resist against the cipher text, the chosen cipher text, and the statistical attacks. Furthermore, increasing the avalanche effect of more than 50% is a promising achievement in comparison to the increased complexities of the proposed method in terms of encryption and decryption processes.
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spelling pubmed-50907802016-11-17 Medical Image Encryption: An Application for Improved Padding Based GGH Encryption Algorithm Sokouti, Massoud Zakerolhosseini, Ali Sokouti, Babak Open Med Inform J Article Medical images are regarded as important and sensitive data in the medical informatics systems. For transferring medical images over an insecure network, developing a secure encryption algorithm is necessary. Among the three main properties of security services (i.e., confidentiality, integrity, and availability), the confidentiality is the most essential feature for exchanging medical images among physicians. The Goldreich Goldwasser Halevi (GGH) algorithm can be a good choice for encrypting medical images as both the algorithm and sensitive data are represented by numeric matrices. Additionally, the GGH algorithm does not increase the size of the image and hence, its complexity will remain as simple as O(n(2)). However, one of the disadvantages of using the GGH algorithm is the Chosen Cipher Text attack. In our strategy, this shortcoming of GGH algorithm has been taken in to consideration and has been improved by applying the padding (i.e., snail tour XORing), before the GGH encryption process. For evaluating their performances, three measurement criteria are considered including (i) Number of Pixels Change Rate (NPCR), (ii) Unified Average Changing Intensity (UACI), and (iii) Avalanche effect. The results on three different sizes of images showed that padding GGH approach has improved UACI, NPCR, and Avalanche by almost 100%, 35%, and 45%, respectively, in comparison to the standard GGH algorithm. Also, the outcomes will make the padding GGH resist against the cipher text, the chosen cipher text, and the statistical attacks. Furthermore, increasing the avalanche effect of more than 50% is a promising achievement in comparison to the increased complexities of the proposed method in terms of encryption and decryption processes. Bentham Open 2016-10-28 /pmc/articles/PMC5090780/ /pubmed/27857824 http://dx.doi.org/10.2174/1874431101610010011 Text en © Sokouti et al.; Licensee Bentham Open https://creativecommons.org/licenses/by/4.0/legalcode This is an open access article licensed under the terms of the Creative Commons Attribution-Non-Commercial 4.0 International Public License (CC BY-NC 4.0) (https://creativecommons.org/licenses/by-nc/4.0/legalcode), which permits unrestricted, non-commercial use, distribution and reproduction in any medium, provided the work is properly cited.
spellingShingle Article
Sokouti, Massoud
Zakerolhosseini, Ali
Sokouti, Babak
Medical Image Encryption: An Application for Improved Padding Based GGH Encryption Algorithm
title Medical Image Encryption: An Application for Improved Padding Based GGH Encryption Algorithm
title_full Medical Image Encryption: An Application for Improved Padding Based GGH Encryption Algorithm
title_fullStr Medical Image Encryption: An Application for Improved Padding Based GGH Encryption Algorithm
title_full_unstemmed Medical Image Encryption: An Application for Improved Padding Based GGH Encryption Algorithm
title_short Medical Image Encryption: An Application for Improved Padding Based GGH Encryption Algorithm
title_sort medical image encryption: an application for improved padding based ggh encryption algorithm
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5090780/
https://www.ncbi.nlm.nih.gov/pubmed/27857824
http://dx.doi.org/10.2174/1874431101610010011
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