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.
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 In the field of Internet, an image is of great significance to information transmission. Meanwhile, how to ensure and improve its security has become the focus of international research. We combine DNA codec with quantum Arnold transform (QArT) to propose a new double encryption algorithm for quantum color images to improve the security and robustness of image encryption. First, we utilize the biological characteristics of DNA codecs to perform encoding and decoding operations on pixel color information in quantum color images, and achieve pixel-level diffusion. Second, we use QArT to scramble the position information of quantum images and use the operated image as the key matrix for quantum XOR operations. All quantum operations in this paper are reversible, so the decryption operation of the ciphertext image can be realized by the reverse operation of the encryption process. We conduct simulation experiments on encryption and decryption using three color images of “Monkey”, “Flower”, and “House”. The experimental results show that the peak value and correlation of the encrypted images on the histogram have good similarity, and the average normalized pixel change rate (NPCR) of RGB three-channel is 99.61%, the average uniform average change intensity (UACI) is 33.41%, and the average information entropy is about 7.9992. In addition, the robustness of the proposed algorithm is verified by the simulation of noise interference in the actual scenario.
In order to increase the security and robustness of quantum images, this study combined the quantum DNA codec with quantum Hilbert scrambling to offer an enhanced quantum image encryption technique. Initially, to accomplish pixel-level diffusion and create enough key space for the picture, a quantum DNA codec was created to encode and decode the pixel color information of the quantum image using its special biological properties. Second, we used quantum Hilbert scrambling to muddle the image position data in order to double the encryption effect. In order to enhance the encryption effect, the altered picture was then employed as a key matrix in a quantum XOR operation with the original image. The inverse transformation of the encryption procedure may be used to decrypt the picture since all the quantum operations employed in this research are reversible. The two-dimensional optical image encryption technique presented in this study may significantly strengthen the anti-attack of quantum picture, according to experimental simulation and result analysis. The correlation chart demonstrates that the average information entropy of the RGB three channels is more than 7.999, the average NPCR and UACI are respectively 99.61% and 33.42%, and the peak value of the ciphertext picture histogram is uniform. It offers more security and robustness than earlier algorithms and can withstand statistical analysis and differential assaults.
Satellite images are critical for ecological monitoring and national security; thus, protecting its integrity is imperative. Nonetheless, existing encryption methods struggle to balance robustness and efficiency. This paper proposes a novel quantum chaos-based image encryption scheme (QCIES) combining a 4D hyperchaotic Lorenz system (4D-HLS) and quantum Fibonacci transform (QFT) addressing these limitations. During the encryption process, we first used The Generalized Quantum Image Representation (GQIR) technique to transform a conventional color image into quantum data. Then, 4D-HLS generates complex, unpredictable keys through bifurcation and sensitivity to initial conditions. 4D-HLS complex dynamics coupled with quantum pixel reorganization provide unprecedented resistance against statistical and brute-force attacks. Additionally, QFT with a quantum adder randomly encrypts pixel locations, producing the final encrypted image. Performance evaluation was conducted using Python to analyze key metrics including histogram distribution, information entropy, and adjacent pixel correlation. Extensive security testing revealed QCIES robust performance, achieving near-ideal correlation coefficients (< 0.004), information entropy (> 7.999), NPCR (99.64%), UACI (33.56%) and massive key space [Formula: see text]. The achieved [Formula: see text] key space notably exceeds the [Formula: see text] NIST standard, while maintaining computational efficiency through optimized quantum circuit design. These innovations establish a new benchmark for satellite image transmission in critical infrastructure applications.
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.
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.
The rapid advancement in consumer technology has led to an exponential increase in the connected devices, resulting in an enormous and continuous flow of data, particularly the image data. This data needs to be processed, managed, and secured efficiently, especially in the quantum-enabled consumer technology era. This paper, in this regards, presents a quantum image encryption scheme featuring a novel two-phase chaotic confusion-diffusion architecture. The proposed architecture consists of four distinct confusion-diffusion modules that perform a simultaneous qubit and pixel-level encryption on both the position and intensity of quantum encoded pixels. Moreover, quantum circuits for′qubit-level chaotic transformation′and′chaos-based selective perfect shuffle operation′have been implemented, which collectively enhance the encryption strength of the proposed scheme. Extensive evaluation has been performed based on various statistical security parameters, such as entropy and correlation. When subjected to differential attacks, the proposed scheme proved its resilience exhibiting ideal results of average 99.6% NPCR (Number of Pixels Change Rate) and 33.5% UACI (Unified Average Changing Intensity). Besides, the proposed scheme also demonstrated resilience against occlusion attacks. Tests involving 50% data occlusion from encrypted images validated the proposed scheme’s capability to successfully decrypt the tampered images, recovering maximum information.