Double layered Fridrich structure to conserve medical data privacy using quantum cryptosystem

Aparna, H.; Bhumijaa, B.; Santhiyadevi, R; Vaishanavi, K; Sathanarayanan, M; Amirtharajan, Rengarajan; Praveenkumar, Padmapriya; El‐Latif, Ahmed A. Abd

doi:10.1016/j.jisa.2021.102972

Cited by 10 publications

(1 citation statement)

References 19 publications

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“…Aparna et al [23] proposed employing quantum cryptography to produce random sequences for the purpose of key stream generation and combining this technique with an adaptive optimization protocol strategy as a means of encrypting medical pictures. Quantum cryptography was used to complete this task successfully.…”

Section: Literature Reviewmentioning

confidence: 99%

A Novel Dual Confusion and Diffusion Approach for Grey Image Encryption using Multiple Chaotic Maps

Praveen,

Suntharam,

Ravi

et al. 2023

IJACSA

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With the exponential growth of the internet and social media, images have become a predominant form of information transmission, including confidential data. Ensuring the proper security of these images has become crucial in today's digital age. This research study proposes a unique strategy for solving this demand by presenting a dual confusion and diffusion technique for encrypting gray-scale pictures. This method is presented as an innovative means of meeting this need. To improve the effectiveness of the encryption process, the encryption method uses several chaotic maps, including the logistic map, the tent map, and the Lorenz attractor. Python is used for the implementation of the suggested approach. Furthermore, a thorough assessment of the encryption mechanism is carried out to determine its efficacy and resilience. By employing the combined strength of chaotic maps and dual confusion and diffusion techniques, the proposed method aims to provide a high level of security for confidential image transmission. The experimental results demonstrate the algorithm's effectiveness in terms of encryption speed, security, and resistance against common attacks. The encrypted images exhibit properties such as randomness, key sensitivity, and resilience against statistical analysis and differential attacks. Moreover, the proposed method maintains a reasonable computational efficiency, and it is compatible with real-time applications. This study makes a contribution to the growing area of picture encryption by presenting an original and effective encryption method that overcomes the shortcomings of previously used approaches. Future work can explore additional security features and extend the proposed approach to encrypt other forms of multimedia data.

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Section: Literature Reviewmentioning

confidence: 99%

A Novel Dual Confusion and Diffusion Approach for Grey Image Encryption using Multiple Chaotic Maps

Praveen,

Suntharam,

Ravi

et al. 2023

IJACSA

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Quantum encryption of healthcare images: Enhancing security and confidentiality in e‐health systems

Kadhim,

Atia

2024

Security and Privacy

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Ensuring the security and privacy of patient data in e‐healthcare systems that rely on cloud computation is of utmost importance. Traditional encryption is no longer resistant to quantum attacks and safeguards sensitive medical images. To tackle this issue, robust security countermeasures are proposed by integrating quantum encryption with a cloud‐based healthcare system. The encryption scheme utilizes the Generalized Novel Enhancement Quantum Representation (GNEQR) and the Novel Enhancement Quantum Representation (NEQR) to provide a framework for representing color and grayscale healthcare images. The proposed quantum algorithm uses quantum logic for image scrambling, which is combined with the encryption key by the Xor quantum gate. The encryption key is generated by 9D chaotic and permutated before encryption. Finally, channel re‐ordering is applied for color images. The simulation results for 15 medical tests with an encryption key space >2600 on a developed e‐healthcare system demonstrate the effectiveness and reliability of the proposed work where the average number of pixels change rates was 99.82, while the unified average change intensity rate was 33.51, entropy was 7.9, the horizontal, vertical, and diagonal correlation coefficients averaged 0.000533333, 0.000706667, and 0.00076, respectively. Finally, the mean squared error (MSE) between the original and encrypted images was 10203.72. These findings improve digital healthcare by revealing the solutions' performance, security, and efficacy.

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Latin Square and Machine Learning Techniques Combined Algorithm for Image Encryption

Patel

Thanikaiselvan

2023

Circuits Syst Signal Process

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Double layered Fridrich structure to conserve medical data privacy using quantum cryptosystem

Cited by 10 publications

References 19 publications

A Novel Dual Confusion and Diffusion Approach for Grey Image Encryption using Multiple Chaotic Maps

A Novel Dual Confusion and Diffusion Approach for Grey Image Encryption using Multiple Chaotic Maps

Quantum encryption of healthcare images: Enhancing security and confidentiality in e‐health systems

Latin Square and Machine Learning Techniques Combined Algorithm for Image Encryption

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