An optical-based encryption and authentication algorithm for color and grayscale medical images

El‐Shafai, Walid; Almomani, Iman; Ara, Anees; Alkhayer, Aala

doi:10.1007/s11042-022-14093-3

Cited by 13 publications

(8 citation statements)

References 51 publications

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“…For our proposed encryption algorithm, the precision of the initial values, which are used to generate the . Reproduced from [60], with permission from Springer Nature chaotic sequences for the encryption process, is set to 10 -15 . This precision allows for a significantly large number of variations in the initial conditions, leading to a correspondingly vast key space.…”

Section: • Key Space Analysismentioning

confidence: 99%

“…These attacks involve the removal of portions of the encrypted image, aiming to disrupt the content and complicate the decryption process. An effective encryption algorithm must ensure that the loss of any part of the image does not irreversibly damage the information, allowing for the restoration of the original image upon decryption [60].…”

Section: • Cropping Attack Analysismentioning

confidence: 99%

“…To underscore the relevance of our proposed method, we conducted a comprehensive comparative analysis against established traditional chaotic encryption techniques in the literature [60,[62][63][64][65]. As shown in table 10, our comparison evaluation focused on the main key metrics critical to the effectiveness and robustness of encryption methods: computational complexity (time in seconds), correlation coefficient, and entropy.…”

Section: • Comparative Analysismentioning

confidence: 99%

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Novel competitive fractional chaotic circuits interaction networks with hierarchical structure and encryption application

El-Mesady,

Elsonbaty,

El-Shafai

et al. 2024

Phys. Scr.

Self Cite

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In the realm of complex networks, the challenge of ensuring secure communication amidst the vulnerabilities of conventional encryption methods has become increasingly critical. This study delves into the complex realm of synchronized behaviors in networks, employing fractional-order chaotic circuits within hierarchically structured competitive interaction networks to enhance encryption security, particularly for medical image transmission. We propose a novel paradigm that transcends traditional synchronization methods used across various disciplines, from engineering to social sciences, by unveiling the intricate dynamics of how units within networks share interactions. Our approach leverages the unique properties of fractional chaos and network hierarchy, demonstrating that the proposed model, characterized by multi-directed links and competitive strategies, significantly improves synchronization. Through detailed analysis, including bifurcation diagrams and Lyapunov exponent plots, we uncover the optimal configurations of coupling strength and fractional order that lead to enhanced network synchronization. This synchronization is pivotal for our encryption application, showcasing a high level of security and privacy in the transmission of medical images. The encryption technique benefits from the network's complex and synchronized dynamics, rendering it a formidable challenge for potential attackers to decipher the encrypted data. While our findings offer a promising mechanism for creating robust communication networks capable of securing sensitive medical data, the implications of our work extend beyond this application. The successful application of fractional-order chaotic circuits sets a groundwork for securing diverse types of data transmissions against the evolving landscape of cyber threats. This research not only marks a significant advancement in network security but also opens new avenues for applying these principles across a spectrum of fields where data security and privacy are paramount.

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Section: • Key Space Analysismentioning

confidence: 99%

Section: • Cropping Attack Analysismentioning

confidence: 99%

Section: • Comparative Analysismentioning

confidence: 99%

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Novel competitive fractional chaotic circuits interaction networks with hierarchical structure and encryption application

El-Mesady,

Elsonbaty,

El-Shafai

et al. 2024

Phys. Scr.

Self Cite

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“…Following 8-bit conversion, the images are grayscaled, ensuring that they are represented in grayscale intensity levels [89]. Grayscaling simplifies the images by reducing them to a single channel, which eliminates color information.…”

Section: Grayscalingmentioning

confidence: 99%

Advanced Medical Image Segmentation Enhancement: A Particle-Swarm-Optimization-Based Histogram Equalization Approach

Saifullah,

Dreżewski

2024

Applied Sciences

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Accurate medical image segmentation is paramount for precise diagnosis and treatment in modern healthcare. This research presents a comprehensive study of the efficacy of particle swarm optimization (PSO) combined with histogram equalization (HE) preprocessing for medical image segmentation, focusing on lung CT scan and chest X-ray datasets. Best-cost values reveal the PSO algorithm’s performance, with HE preprocessing demonstrating significant stabilization and enhanced convergence, particularly for complex lung CT scan images. Evaluation metrics, including accuracy, precision, recall, F1-score/Dice, specificity, and Jaccard, show substantial improvements with HE preprocessing, emphasizing its impact on segmentation accuracy. Comparative analyses against alternative methods, such as Otsu, Watershed, and K-means, confirm the competitiveness of the PSO-HE approach, especially for chest X-ray images. The study also underscores the positive influence of preprocessing on image clarity and precision. These findings highlight the promise of the PSO-HE approach for advancing the accuracy and reliability of medical image segmentation and pave the way for further research and method integration to enhance this critical healthcare application.

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“…Hash-based message authentication code (HMAC) was addressed in [20], in which the authors focused on the authentication of images from the healthcare domain. They proposed an optical algorithm that ensures the efficiency and security of medical image transmission.…”

Section: Cryptography-based Image Authenticationmentioning

confidence: 99%

Steganography Approach to Image Authentication Using Pulse Coupled Neural Network

Forgáč,

Očkay,

Javurek

et al. 2023

cai

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This paper introduces a model for the authentication of large-scale images. The crucial element of the proposed model is the optimized Pulse Coupled Neural Network. This neural network generates position matrices based on which the embedding of authentication data into cover images is applied. Emphasis is placed on the minimalization of the stego image entropy change. Stego image entropy is consequently compared with the reference entropy of the cover image. The security of the suggested solution is granted by the neural network weights initialized with a steganographic key and by the encryption of accompanying steganographic data using the AES-256 algorithm. The integrity of the images is verified through the SHA-256 hash function. The integration of the accompanying and authentication data directly into the stego image and the authentication of the large images are the main contributions of the work.

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An optical-based encryption and authentication algorithm for color and grayscale medical images

Cited by 13 publications

References 51 publications

Novel competitive fractional chaotic circuits interaction networks with hierarchical structure and encryption application

Novel competitive fractional chaotic circuits interaction networks with hierarchical structure and encryption application

Advanced Medical Image Segmentation Enhancement: A Particle-Swarm-Optimization-Based Histogram Equalization Approach

Steganography Approach to Image Authentication Using Pulse Coupled Neural Network

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