Image scrambling methods are necessary for original image processes in applications of quantum image processing like quantum image encryption, which increases the strength of the encryption process, and the resulting image is difficult to identify and detect its details.As well as obtain a high entropy value and a histogram with a uniform peak for the encrypted image.Most researches focus on scrambling the position only or the value only; however, the quantum image scrambling researches focused on scrambling both position and value together is few.The idea of the study is developing a genetic algorithm to generate different schemes of scrambling based on the fast and elementary schemes with changing the quantum logical gate (NOT / C-Not) to get the best scheme that meets the requirements such as the cost, the complexity or the type of the image.One of the essential benefits of the proposed work is developing a general framework for the automatic generation of a suitable scrambling scheme based on image type, method, and logical circuit.The tests are simulated using MATLAB.The result confirms that hybrid value/position schemes with a C-Not gate have an entropy value close to 8 and a flat histogram.It is implicated that this framework will benefit many researchers in selecting the most appropriate scrambling method for their works.
Image scrambling methods are necessary for original image processes in applications of quantum image processing like quantum image encryption, which increases the strength of the encryption process, and the resulting image is difficult to identify and detect its details.As well as obtain a high entropy value and a histogram with a uniform peak for the encrypted image.Most researches focus on scrambling the position only or the value only; however, the quantum image scrambling researches focused on scrambling both position and value together is few.The idea of the study is developing a genetic algorithm to generate different schemes of scrambling based on the fast and elementary schemes with changing the quantum logical gate (NOT / C-Not) to get the best scheme that meets the requirements such as the cost, the complexity or the type of the image.One of the essential benefits of the proposed work is developing a general framework for the automatic generation of a suitable scrambling scheme based on image type, method, and logical circuit.The tests are simulated using MATLAB.The result confirms that hybrid value/position schemes with a C-Not gate have an entropy value close to 8 and a flat histogram.It is implicated that this framework will benefit many researchers in selecting the most appropriate scrambling method for their works.
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.
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.
Given the limitations of current classic image encryption algorithms and the unconditional security characteristics of quantum key distribution protocols, the author proposes an image encryption method based on quantum key distribution and pixel scrambling. The author first analyzed the security issues of quantum image encryption algorithms based on image scrambling methods, namely that image scrambling methods have periodicity, which can ensure that the image can be restored after scrambling. If an image cannot be guaranteed to return to its original state after performing scrambling operations, legitimate users cannot obtain the secret information in the original image, and image scrambling loses its original meaning; However, the periodicity of image scrambling methods not only ensures that legitimate users can decrypt images, but also provides convenience for attackers to steal original image information. Secondly, it is pointed out that when evaluating and analyzing quantum image encryption algorithms, the evaluation indicators should include two parts: One is performance analysis, which is the analysis of the network complexity of quantum circuits. In quantum computing, the network complexity of quantum circuits is usually represented by the number of quantum basic logic gates. The second is security analysis, which mainly includes key analysis (including key space size and key sensitivity analysis), statistical analysis (including pixel correlation, histogram analysis, information fusion, and scatter plot distribution density analysis). Finally, experimental simulations have shown that the NPCR values of the plaintext and ciphertext images of the three images tend to 100%. The encrypted image histogram is evenly distributed, with very weak pixel correlation and high pixel change rate and information entropy.
Secure image transmission has become critical in the emerging quantum computing landscape. This research introduces a hybrid key quantum encryption approach that combines Quantum True Random Number Generation (QTRNG) and Quantum Pseudo Random Number Generation (QPRNG) to enhance security and efficiency. The proposed Quantum Hybrid Random Number Generator (QHRNG) integrates entanglement-based true randomness with structured pseudo-randomness using Hadamard, controlled rotation and Clifford gates to generate high-entropy encryption keys. The generated Quantum keys are applied to encrypt grayscale images using the Novel Enhanced Quantum Image Representation (NEQR). The encryption process is strengthened by quantum bit-level scrambling and selective Quantum Fourier Transform. The proposed method is implemented on Qiskit’s Aer and Basic simulators and validated on IBM’s torino quantum hardware. Compared to standalone QTRNG and QPRNG methods, QHRNG consistently provides higher randomness and stronger security in noisy and noiseless environments. This work offers a robust and future-ready framework for quantum secure image encryption.
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.
The paper proposes a lossless quantum image encryption scheme based on substitution tables (S-box) scrambling, mutation operation and general Arnold transform with keys. First, the key generator builds upon the foundation of SHA-256 hash with plain-image and a random sequence. Its output value is used to yield initial conditions and parameters of the proposed image encryption scheme. Second, the permutation and gray-level encryption architecture is built by discrete Arnold map and quantum chaotic map. Before the permutation of Arnold transform, the pixel value is modified by quantum chaos sequence. In order to get high scrambling and randomness, S-box and mutation operation are exploited in gray-level encryption stage. The combination of linear transformation and nonlinear transformation ensures the complexity of the proposed scheme and avoids harmful periodicity. The simulation shows the cipher-image has a fairly uniform histogram, low correlation coefficients closed to 0, high information entropy closed to 8. The proposed cryptosystem provides 2256 key space and performs fast computational efficiency (speed = 11.920875 Mbit/s). Theoretical analyses and experimental results prove that the proposed scheme has strong resistance to various existing attacks and high level of security.