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Security and Privacy

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

Ahmed J. Kadhim, Tayseer Salman Atia

Published Apr 18, 2024• 4 citations
Publisher

Abstract

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.

DOI
10.1002/spy2.391

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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.
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.
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.
ABSTRACT The rapid development of healthcare system has increased the necessities for the secure medical image transmission. As quantum computers develop, classical cryptographic techniques become vulnerable to quantum attacks. This paper proposes QKD assisted quantum encryption for medical images. BB84 protocol is utilised to generate a secure shared key, which is further enhanced using Henon maps. The logistic map whose parameters are derived from the shared key is employed to generate the permutation sequence for pixel values. Medical images are encoded using the novel enhanced quantum representation (NEQR) and encrypted via quantum permutation and quantum XOR operations employing block‐wise strategy. The proposed method was evaluated in both ideal and noisy quantum environments such as amplitude damping, depolarising, bit‐flip and phase damping noise models. The experimental results show strong security performance on a benchmark and medical images with high entropy values, near zero‐pixel correlation and resistance to differential attacks. Additionally, noise analysis shows that bit‐flip and amplitude damping noises affect the image reconstruction more than phase damping and depolarising noise. Overall, the proposed framework provides a secure solution for medical image security.
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.
Quantum computing introduces major threats to conventional image encryption methods, especially in medical contexts. This paper addresses these threats by developing a quantum-resistant encryption scheme for medical images. We present a novel framework combining: (1) a novel Mixed Logistic-Ikeda-Henon (MLIH) chaotic map for pseudorandom key generation, (2) quantum image representation using the Novel Enhanced Quantum Representation (NEQR) model, and (3) a two-stage encryption process employing Controlled-Not (CNOT) gate chaining for diffusion and One-Time Pad (OTP) with MLIH-generated keys for confusion. The RGB channels are processed separately through quantum state conversion, CNOT-based diffusion, and keyed confusion before final recombination. To validate practical feasibility, the proposed encryption scheme was implemented on IBM’s 127-qubit ibm_sherbrooke quantum processor, demonstrating real-world feasibility. Experimental validation shows near-ideal entropy (7.9977), superior NPCR (99.97%) and UACI (33.89%) values, and an expansive key space (2 1952 ). The novel MLIH demonstrates a 12.7% improvement in logic gate efficiency compared to conventional chaotic and the image encryption has quantum advantage through parallel CNOT operations. The hardware execution yielded a throughput of 4,500 Circuit Layer Operations Per Second (CLOPS), indicating efficient real-time performance on NISQ devices, Moreover, the echoed cross-resonance (ECR) gate error remained within a median of 1.1 × 10⁻ 2 , supporting reliable circuit execution. The proposed scheme outperforms contemporary quantum and classical encryption approaches in terms of entropy, NPCR, UACI, and key sensitivity, all while maintaining a computational complexity of O(n), ensuring scalability. This study effectively bridges the gap between theoretical quantum security models and real-world implementation on existing NISQ devices, demonstrating resilience against classical statistical and differential attacks, as well as quantum-specific threats such as Grover’s brute-force search and quantum chosen-plaintext attacks. The successful deployment of IBM quantum hardware positions this scheme as a viable solution for secure medical image transmission in quantum-era healthcare systems.