Medical image encryption using fractional discrete cosine transform with chaotic function

Kumar, Sumit; Panna, Bhaskar; Jha, Rajib Kumar

doi:10.1007/s11517-019-02037-3

Cited by 96 publications

(48 citation statements)

References 54 publications

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“…The cosine transform is a very useful mathematical tool that is used in applications of signal and optical processing, such as filtering, encryption, compression and recognition [1][2][3][4][5][6][7][8][9]. The finite fields are special mathematical structures based on integer numbers, which are used in image and video watermarking; digital data coding and decoding with detection and correction of errors in communication systems; estimation; compression; filtering and encryption of signals and images; and other applications [10][11][12][13][14][15].…”

Section: Introductionmentioning

confidence: 99%

Image Encryption and Decryption Systems Using the Jigsaw Transform and the Iterative Finite Field Cosine Transform

2019

Photonics

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We propose the use of the Jigsaw transform (JT) and the iterative cosine transform over a finite field in order to encrypt and decrypt images. The JT is a nonlinear operation that allows one to increase the security over the encrypted images by adding new keys to the encryption and decryption systems. The finite field is a finite set of integer numbers where the basic mathematical operations are performed using modular arithmetic. The finite field used in the encryption and decryption systems has an order given by the Fermat prime number 257. The iterative finite field cosine transform (FFCT) was used in our work with the purpose of obtaining images that had an uniform random distribution. We used a security key given by an image randomly generated and uniformly distributed. The JT and iterative FFCT was utilized twice in the encryption and decryption systems. The encrypted images presented a uniformly distributed histogram and the decrypted images were the same original images used as inputs in the encryption system. The resulting decrypted images had a high level of image quality in comparison to the image quality of the decrypted images obtained by the actual optical decryption systems. The proposed encryption and decryption systems have three security keys represented by two random permutations used in the JTs and one random image. The key space of the proposed encryption and decryption systems is larger. The previous features of the security system allow a better protection of the encrypted image against brute force and statistical analysis attacks.

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Section: Introductionmentioning

confidence: 99%

Image Encryption and Decryption Systems Using the Jigsaw Transform and the Iterative Finite Field Cosine Transform

2019

Photonics

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“…We compare both images to detect a correlation between the plain image and the encrypted image. Using a practical algorithm, -0.0012 0.0099 -0.0032 [24] 0.0027 0.0015 0.0019 [25] 0.0023 -0.0010 0.0009 [26] 0.0944 0.0057 0.0067 [15] 0.0098 -0.0078 0.0181…”

Section: Analysis Of Differential Attackmentioning

confidence: 99%

“…The results show that our proposed algorithm is highly capable of resisting differential attacks. [23] 99.610 33.261 [24] 99.532 33.450 [25] 99.51 33.39 [26] 99.79 33.16 [15] 99.6067 33.4954…”

Section: Analysis Of Differential Attackmentioning

confidence: 99%

A New Image Encryption Algorithm for Grey and Color Medical Images

et al. 2021

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Recently, diagnosing diseases using medical images became crucial. As these images are transmitted through the network, they need a high level of protection. If the data in these images are liable for unauthorized usage, this may lead to severe problems. There are different methods for securing images. One of the most efficient techniques for securing medical images is encryption. Confusion and diffusion are the two main steps used in encryption algorithms. This paper presents a new encryption algorithm for encrypting both grey and color medical images. A new image splitting technique based on image blocks introduced. Then, the image blocks scrambled using a zigzag pattern, rotation, and random permutation. Then, a chaotic logistic map generates a key to diffuse the scrambled image. The efficiency of our proposed method in encrypting medical images is evaluated using security analysis and time complexity. The security is tested in entropy, histogram differential attacks, correlation coefficient, PSNR, keyspace, and sensitivity. The achieved results show a high-performance security level reached by successful encryption of both grey and color medical images. A comparison with various encryption methods is performed. The proposed encryption algorithm outperformed the recent existing encryption methods in encrypting medical images.

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“…Data encryption is usually done by chaotic or hyper-chaotic methods [ 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 ]. In some researches, chaotic or hyper-chaotic systems are used to encrypt peripheral data [ 38 , 39 , 40 , 41 , 42 , 43 ].…”

Section: Introductionmentioning

confidence: 99%

Medical Images Encryption Based on Adaptive-Robust Multi-Mode Synchronization of Chen Hyper-Chaotic Systems

Javan

Jafari

Shoeibi

et al. 2021

Sensors

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In this paper, a novel medical image encryption method based on multi-mode synchronization of hyper-chaotic systems is presented. The synchronization of hyper-chaotic systems is of great significance in secure communication tasks such as encryption of images. Multi-mode synchronization is a novel and highly complex issue, especially if there is uncertainty and disturbance. In this work, an adaptive-robust controller is designed for multimode synchronized chaotic systems with variable and unknown parameters, despite the bounded disturbance and uncertainty with a known function in two modes. In the first case, it is a main system with some response systems, and in the second case, it is a circular synchronization. Using theorems it is proved that the two synchronization methods are equivalent. Our results show that, we are able to obtain the convergence of synchronization error and parameter estimation error to zero using Lyapunov’s method. The new laws to update time-varying parameters, estimating disturbance and uncertainty bounds are proposed such that stability of system is guaranteed. To assess the performance of the proposed synchronization method, various statistical analyzes were carried out on the encrypted medical images and standard benchmark images. The results show effective performance of the proposed synchronization technique in the medical images encryption for telemedicine application.

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Medical image encryption using fractional discrete cosine transform with chaotic function

Cited by 96 publications

References 54 publications

Image Encryption and Decryption Systems Using the Jigsaw Transform and the Iterative Finite Field Cosine Transform

Image Encryption and Decryption Systems Using the Jigsaw Transform and the Iterative Finite Field Cosine Transform

A New Image Encryption Algorithm for Grey and Color Medical Images

Medical Images Encryption Based on Adaptive-Robust Multi-Mode Synchronization of Chen Hyper-Chaotic Systems

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