This study presents a pioneering quantum encryption technique, the Generalized Novel Enhancement Quantum Representation (GNEQR), to ensure enhanced security for color medical images in E-health systems. The proposed method is seamlessly integrated into an ASP.NET Web API and Blazor Web Assembly environment. During the encryption process, the GNEQR algorithm utilizes advanced bit-plane scrambling to obscure the original color medical image. A 5D chaotic map is employed to generate an image key, which is then used to create a scrambled version of the key image. Applying an XOR operation between the scrambled image and the key image produces a highly secure quantum-encrypted color image. In the decryption process, the inverse of the encryption steps is implemented, leveraging the 5D chaotic map-generated key to accurately reconstruct the original color medical image. This research aims to significantly enhance E-health security by protecting patient data, including medical images and histories, through quantum encryption. The incorporation of GNEQR within an ASP.NET Web API and Blazor Web Assembly framework facilitates seamless deployment and underscores the potential of this method to revolutionize healthcare data privacy and integrity.
This study presents a pioneering quantum encryption technique, the Generalized Novel Enhancement Quantum Representation (GNEQR), to ensure enhanced security for color medical images in E-health systems. The proposed method is seamlessly integrated into an ASP.NET Web API and Blazor Web Assembly environment. During the encryption process, the GNEQR algorithm utilizes advanced bit-plane scrambling to obscure the original color medical image. A 5D chaotic map is employed to generate an image key, which is then used to create a scrambled version of the key image. Applying an XOR operation between the scrambled image and the key image produces a highly secure quantum-encrypted color image. In the decryption process, the inverse of the encryption steps is implemented, leveraging the 5D chaotic map-generated key to accurately reconstruct the original color medical image. This research aims to significantly enhance E-health security by protecting patient data, including medical images and histories, through quantum encryption. The incorporation of GNEQR within an ASP.NET Web API and Blazor Web Assembly framework facilitates seamless deployment and underscores the potential of this method to revolutionize healthcare data privacy and integrity.
Abstract 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.
Security of medical media is important for patient safety and confidentiality. This paper proposes a framework for the chaos-based quantum encryption of healthcare images. In the framework, healthcare staff in one location send cipher images to the cloud. The healthcare staff in another location receives the images from the cloud. By decrypting the content of the images, the healthcare staff can assist users in a secure manner. This paper also proposes a novel approach for the efficient quantum image encryption of healthcare media. The proposed algorithm utilizes gray code and a chaotic map. The quantum image is scrambled by quantum gray code. Then, the scrambled quantum image is encrypted using a quantum XOR operation based on a key generator controlled by the logistic-sine map. The circuits of the proposed encryption/decryption algorithm are devised based on an NEQR quantum image representation. Numerical and simulation analyses show that the proposed quantum image encryption approach is robust, realizable, and has high efficiency compared with its classical counterpart.
Ensuring patient secrecy and maintaining data integrity are critical in healthcare information security. With increasing demands for stronger protection in the management and storage of medical images, this study introduces an innovative framework utilizing chaos-based quantum encryption for enhanced security. This approach combines a DNA codec with the QFBT (Quantum Fibonacci Transform), creating a unique dual-encryption method for quantum color images. The process begins with converting a standard color image to quantum data through GQIR (Generalized Quantum Image Representation) technique. A DNA codec then encodes and decodes the pixel color data of the quantum image, achieving pixel-level diffusion. Finally, the QFBT is applied to scramble the image's spatial data. The resulting transformed image is then used as the key matrix in quantum XOR functions. Findings from the experiment indicate that both the correlation and peak value of the encrypted image histograms show strong similarity. The mean NPCR (Normalized Pixel Change Rate) for the RGB channels is 99.63%, while UACI (Uniform Average Change Intensity) is 33.43%. Additionally, the mean information entropy is approximately 7.9992. These findings demonstrate the effectiveness of QDIES in providing robust security for medical image data.
Medical image security is crucial for patient confidentiality because it is exposed to many attacks, such as editing photos or moving the affected part to another place, and others. Encryption is an efficient technique to protect the confidentiality of images, but traditional encryption suffers from brute-force attacks. This research proposes an encryption method depending on quantum concepts to resist brute-force attacks using a 3D logistic map to generate keys; the keys were scrambled to increase the randomness, and using the best image scrambling scheme generated by a genetic algorithm as a first stage to increase the strength of the encryption algorithm. The quantum scrambled image is then encrypted by using XOR process depending on a 3D logistic map key generator. The proposed encrypting and decrypting algorithm utilize a NEQR quantum image representation. Numerical and simulation analyses using MATLAB demonstrate that the suggested encryption algorithm is robust, realizable, and highly efficient in comparison to its classical equivalent.
With the growing demand for highly secure medical data transmission, this research introduces a fused cryptography framework that integrates mathematical quantum computing operations with advanced classical encryption techniques. The proposed method incorporates quantum principles, including quantum walks, quantum-based cyclic shift operators, quantum XOR operations, and quantum key image generation with classical methods such as bit-plane extraction and hyperchaotic system-based scrambling. A hyperchaotic map generates random key sequences to produce both a spatial domain random image and a quantum key image. The medical image is first decomposed into eight bit-planes, and only the high-information bit-planes (HIBPs) undergo encryption to optimize computational efficiency. HIBPs are scrambled using multilayer, block-wise, and diagonal permutations based on the chaotic sequences. Quantum encryption is then applied, starting with novel enhanced quantum representation encoding, followed by Baker map-based scrambling and quantum XOR diffusion to secure the final ciphertext. Extensive experiments, including entropy evaluation, noise attack resilience, clipping attack robustness, and correlation analysis, confirm the superior security and performance of the proposed method. Notably, the algorithm achieves near-ideal results, such as an entropy of 7.9999, a correlation coefficient of 0.0001, 98% plaintext recovery after 30% noise corruption, and 96% recovery after 25% ciphertext clipping, demonstrating its robustness for secure medical data transmission.
Healthcare requires data encryption to safeguard sensitive patient information from unauthorized access or breaches. Encryption ensures that data is encoded into a secure format, making it unreadable to anyone without the decryption key. This helps maintain patient privacy, protects against identity theft, and ensures compliance with data protection regulations like HIPAA (Health Insurance Portability and Accountability Act.). With encryption, healthcare organizations can mitigate the risk of data breaches and uphold trust with patients by ensuring the confidentiality and integrity of their medical records and personal information. Quantum cryptography emerges as a revolutionary solution, offering unparalleled encryption for healthcare data. This process initiates with the meticulous crafting of quantum states to encapsulate healthcare data securely, ensuring precise encoding. Subsequently, quantum entanglement is established between sender and receiver, creating a secure communication channel resistant to interception attempts. Quantum key distribution then generates a secure key leveraging entangled quantum states, becoming the cornerstone of encryption. Quantum encryption shields healthcare data in an impenetrable veil of secrecy, leveraging the complexities of quantum mechanics to thwart unauthorized decryption attempts. The decryption process, facilitated by the shared secure key, unveils the encrypted healthcare data exclusively to authorized parties, preserving confidentiality with unparalleled precision. The result reveals quantum cryptography's superiority in healthcare data encryption. At 150-bit key length, quantum cryptography takes 352,237 milliseconds vs. AES's 310,285 milliseconds. For a 14 KB input, quantum cryptography requires 7 milliseconds compared to AES's 12 milliseconds. These metrics highlight quantum cryptography's efficiency gains and transformative potential in healthcare data security, promising both enhanced security and efficiency benefits.