Background: Quantum image processing is rapidly developing in the field of quantum computing, and it can be successfully implemented on the Noisy Intermediate-Scale Quantum (NISQ) device. Quantum image encryption holds a pivotal position in this domain. However, the encryption process often encounters security vulnerabilities and entails complex computational complexities, thereby consuming substantial quantum resources. To address this, the present study proposes a quantum image encryption algorithm based on four-dimensional chaos. Methods: The classical image is first encoded into quantum information using the Generalized Quantum Image Representation (GQIR) method. Subsequently, the trajectory of the four-dimensional chaotic system is randomized, and multi-dimensional chaotic keys are generated to initially encrypt the pixel values of the image. Then, the Arnold transformation is applied to randomly encrypt the pixel positions, resulting in the encrypted image. During the decryption process, the inverse process of encryption is employed to restore the original image. Results: We simulated this process in the Python environment, and the information entropy analysis experiment showed that the information entropy of the three encrypted images reached above 7.999, so the system has good encryption. At the same time, the correlation of the pixel distribution after the encryption algorithm is weak, which proves that the control parameters of the chaotic system can effectively reduce the correlation between pixels in the image. In the final key space analysis, the key space issued by our encryption can reach $10 140 \gg 2 128 $. Conclusion: Our method is resistant to destructive attacks and can produce scrambled images with higher encryption and usability. This algorithm solves the problems of general encryption algorithms such as periodicity, small key space, and vulnerability to statistical analysis, and proposes a reliable and effective encryption scheme. By making full use of the characteristics of Arnold transformation permutation, ergodicity and the randomness of the four-dimensional chaotic system, the encryption algorithm uses the larger key space provided by the four-dimensional Lorenz system.
Background: Quantum image processing is rapidly developing in the field of quantum computing, and it can be successfully implemented on the Noisy Intermediate-Scale Quantum (NISQ) device. Quantum image encryption holds a pivotal position in this domain. However, the encryption process often encounters security vulnerabilities and entails complex computational complexities, thereby consuming substantial quantum resources. To address this, the present study proposes a quantum image encryption algorithm based on four-dimensional chaos. Methods: The classical image is first encoded into quantum information using the Generalized Quantum Image Representation (GQIR) method. Subsequently, the trajectory of the four-dimensional chaotic system is randomized, and multi-dimensional chaotic keys are generated to initially encrypt the pixel values of the image. Then, the Arnold transformation is applied to randomly encrypt the pixel positions, resulting in the encrypted image. During the decryption process, the inverse process of encryption is employed to restore the original image. Results: We simulated this process in the Python environment, and the information entropy analysis experiment showed that the information entropy of the three encrypted images reached above 7.999, so the system has good encryption. At the same time, the correlation of the pixel distribution after the encryption algorithm is weak, which proves that the control parameters of the chaotic system can effectively reduce the correlation between pixels in the image. In the final key space analysis, the key space issued by our encryption can reach 10140≫2128. Conclusion: Our method is resistant to destructive attacks and can produce scrambled images with higher encryption and usability. This algorithm solves the problems of general encryption algorithms such as periodicity, small key space, and vulnerability to statistical analysis, and proposes a reliable and effective encryption scheme. By making full use of the characteristics of Arnold transformation permutation, ergodicity and the randomness of the four-dimensional chaotic system, the encryption algorithm uses the larger key space provided by the four-dimensional Lorenz system.
In the wake of the information security era, ensuring the privacy, accuracy, and reliability of images has become imperative. In this paper, a quantum image encryption method combining quantum Arnold transform and a hyper 5D chaotic system is devised. Furthermore, first, a nonlinear color quantization model (NCQI) is used to convert digital images in standard RGB format into quantum color images. Then, based on the size of the converted quantum color image, the corresponding encryption key is generated using the hyper 5D chaotic system. In the encryption stage, we use the key to encrypt the converted quantum color image. This process entails two principal steps: First, we use quantum Arnold transform to scramble the pixel positions in the image and, subsequently, diffuse the pixel values through a carefully designed cyclic shift strategy to achieve the preliminary encryption of the image. To further strengthen the encryption security, we use a quantum rotation gate to perform quantum rotation transformation on the color channel of each pixel point in the encrypted image separately. These well-designed encryption processes, in succession, significantly enhance the security of the image. This paper provides the corresponding quantum circuit design and validates both the efficacy and security of the quantum image encryption scheme through simulation experimental results.
Objectives. The aim of the work is the development and experimental verification of a hybrid postquantum image encryption algorithm based on a 3D chaotic system and the Rubik's cube principle. Methods. Issues of the vulnerability of traditional encryption methods to attacks using quantum computers are considered. To create a cryptographically robust algorithm, it is proposed to combine the advantages of chaotic systems and quantum computing. A new 3D chaotic system based on a modified Lorenz system is used for generating pseudorandom keys. The Rubik's cube principle is applied to perform image scrambling operations (cyclic shifting of rows and columns). The NEQR (Novel Enhanced Quantum Representation) model is used for quantum representation and data processing. The algorithm is implemented in Python using the Quiskit, OpenCV, and NumPy libraries, as well as the AerSimulator quantum computing simulator. Results. A hybrid encryption algorithm has been developed and implemented as a computer program. The algorithm was tested on images of various sizes and formats. Resistance to statistical and differential attacks has been experimentally confirmed: the correlation coefficient of adjacent pixels in the encrypted images is close to zero, the information entropy is close to the ideal value of 8, and the NPCR and PSNR values exceed 99,25 % and are less than 13 dB, respectively. Conclusion. The proposed hybrid algorithm demonstrates high cryptographic strength and efficiency. Key sensitivity, the use of quantum principles, and performance optimization through multithreading make it practical for use in security-critical areas such as IoT, telemedicine, and cloud storage. The software implementation operates locally without requiring an internet connection, which ensures data security.
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 In recent years, extensive research has been conducted on encryption algorithms based on square images. However, relatively few studies have evaluated nonsquare images. In this paper, we propose a novel encryption algorithm for nonequal length images. This algorithm incorporates bitplane chaotic mapping and Arnold transformation. To implement the algorithm effectively, we first transform the plain image into two binary sequences of equal size. Then, we introduce a new diffusion strategy to mutually diffuse these two sequences. Next, we utilize a chaotic map to control the swapping of binary elements between the two sequences. This process allows for the permutation of bits from one bitplane to any other bitplane. Finally, we employ the Arnold transform to scramble the positional information of the image, resulting in the final encrypted image. Using the parameters of nonequal Arnold transformation and the initial value of the Lorenz chaotic map as keys not only simplify the transmission of keys, but also makes the cryptosystem have infinite key space for resisting brute force attacks. Experimental results and security analysis verify that the proposed quantum image encryption algorithm can encrypt nonsquare images, and has good performance in terms of nonstatistical properties, key sensitivity, robustness and so on. Moreover, simulation experiments based on Qiskit successfully verify the correctness and feasibility of the quantum image encryption algorithm.
In order to improve the security of quantum color images, this study proposes a novel algorithm for quantum color image encryption based on three-dimensional chaotic systems. The encrypted quantum color image is represented by the novel quantum image representation for color digital image model. The original image is first perturbed by the Arnold transform and then the RGB channel is perturbed separately from the chaotic sequence generated by the new three-dimensional chaotic system by the xor operation. Evaluation metrics such as histogram, information entropy, and correlation of neighboring pixels of the image are analyzed using MATLAB. The simulation results show that the pixel values of the encrypted image are uniformly distributed and the algorithm enhances the security of quantum color images. The specific quantum circuit diagram of the encryption algorithm is given in the paper. The superposition and entanglement properties of quantum physics greatly improve the efficiency of complex image processing algorithms, and the overall complexity of the circuit is O(n), which is efficient and implementable.
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.