Smartphone application for medical images secured exchange based on encryption using the matrix product and the exclusive addition

Boussif, Mohamed; Aloui, Noureddine; Cherif, Adnane

doi:10.1049/iet-ipr.2017.0229

Cited by 19 publications

(12 citation statements)

References 29 publications

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“…The authors Mohamed Boussif1 et al, [9] provide a secure medical picture transfer technique via a smartphone in this work, which is based on a suggested image encryption technique that uses the matrix product and exclusive addition. This study is unique in that it presents a low-complexity encryption method that can run on an embedded system in real time.…”

Section: Survey Of Literaturementioning

confidence: 99%

Subject Review:Encryptionof Image in the Android Environment in Various Algorithms

Ridha¹,

Jabar²,

AL-Qinani³

2021

IJERAT

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In the vast and still evolving the world of digital transfer, data/image security is one of the most important considerations. One method is to encrypt files. One of the well-known mechanisms for maintaining privacy of pictures to a trustworthy, unrestricted public, the media as a result, this medium is vulnerable to attacks, Encryption algorithms that are effective are a must for data transfer that is stable a variety of techniques. This paper is a study of research authors in the field of image encryption for the Android Environment for different algorithms, with a research review for the period (2010)(2011)(2012)(2013)(2014)(2015)(2016)(2017)(2018)(2019)(2020)(2021) to see how the field of image encryption has progressed and the best algorithms in their performance.

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Section: Survey Of Literaturementioning

confidence: 99%

Subject Review:Encryptionof Image in the Android Environment in Various Algorithms

Ridha¹,

Jabar²,

AL-Qinani³

2021

IJERAT

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“…Boussif et al . [54] designed an image encryption approach for medical images. In this approach, the exclusive addition and matrix product are used to perform the image encryption.…”

Section: Introductionmentioning

confidence: 99%

Parallel strength Pareto evolutionary algorithm‐II based image encryption

2020

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In recent years, many image encryption approaches have been proposed on the basis of chaotic maps. The various types of chaotic maps such as one‐dimensional and multi‐dimensional have been used to generate the secret keys. Chaotic maps require some parameters and value assignment to these parameters is very crucial. Because, poor value assignments may make the chaotic map un‐chaotic. Therefore, hyper‐parameter tuning of chaotic maps is required. Recently, meta‐heuristic based image encryption approaches have been designed by researchers to resolve this issue. However, the majority of the techniques suffer from poor computational speed and stuck in local optima problems. Therefore, in this study, a strength Pareto evolutionary algorithm‐II based meta‐heuristic approach is proposed to tune the hyper‐parameters of the four‐dimensional chaotic map. The proposed approach is also implemented in a parallel fashion to enhance the computational speed. The effectiveness of the proposed approach is evaluated through extensive experiments. Comparative analyses show that the proposed approach outperforms the competitive approaches in terms of entropy, NPCR, UACI, and PSNR by 0.9834, 1.0728, 0.9134, and 0.8971normal%, respectively.

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“…With the widespread use of multimedia communications and the rapid development of cloud technologies, images are stored and transmitted over the internet as an important carrier of information. In recent years, with the digital image privacy data leakage incidents continuing to occur, the secure transmission and storage of private information have become an important issue [1–5]. Owing to some special properties of images such as large data capacity, strong correlation of pixel points and high redundancy, lots of problems in encryption efficiency, computing resources and real‐time transmission have turned up in traditional data encryption algorithms of the advanced encryption standard (AES), data encryption standard (DES), Rivest‐Shamir‐Adleman (RSA), making them not suitable for image encryption [6, 7].…”

Section: Introductionmentioning

confidence: 99%

Image encryption algorithm based on image hashing, improved chaotic mapping and DNA coding

Zhang

Han

2019

IET image process

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In order to improve the problems of security and robustness for existing image encryption algorithms and to reduce the security risks of encryption algorithms against statistical analysis, differential attacks, exhaustive attacks, cropping and noise attacks etc., a novel image encryption algorithm based on image hashing, improved chaotic mapping and DNA coding is proposed. Firstly, extracting the image features and evenly block after pre‐processing the original image and fingerprint image. Secondly, the features are generated to be a binary hash sequence through the image hash algorithm, and the generated hash sequence is iterated as the initial parameter of the improved chaotic map and Chen's chaotic system. Finally, Chen's chaotic system is used to generate a random sequence, and the matrix generated by the improved chaotic map and the original image is subjected to DNA calculation and encoding operations to obtain an encrypted image. Experimental results show that the proposed algorithm has better performance on security, larger key space and higher key sensitivity, the pixel correlation coefficient close to 0, the information entropy close to 8, unified average changing intensity and number of pixels change rate values are close to ideal values, and it has better robustness on noise and cropping attacks.

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Smartphone application for medical images secured exchange based on encryption using the matrix product and the exclusive addition

Cited by 19 publications

References 29 publications

Subject Review:Encryptionof Image in the Android Environment in Various Algorithms

Subject Review:Encryptionof Image in the Android Environment in Various Algorithms

Parallel strength Pareto evolutionary algorithm‐II based image encryption

Image encryption algorithm based on image hashing, improved chaotic mapping and DNA coding

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