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.
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.
Images are important data carriers because, compared to text data, they are harder to transfer or store securely and include higher volumes and redundancies of digital data. Images can be shielded against a variety of risks with security, including eavesdropping and illegal copying and alteration. Because of the potential quantum risk to the existing cryptographic encryption methods and the quick advancement towards the development of quantum computers, quantum image encryption algorithms have recently drawn increasing amounts of attention. The majority of quantum image encryption techniques such as diffusion and scrambling, involve two separate rounds. In this model, the three different chaotic maps are used separately for scrambling the images to determine the performance of the quantum image cryptography with different combination of the model. At first, the hash256 algorithm is used for generating the quantum key and the forward diffusion takes place for diffusing the first pixel to final pixel of the input image information. Then, the three different chaotic maps such as pixel permutation, Chen attractor and Lorenz attractor are used for scrambling the input image. Finally, the bit-level permutation and backward diffusion process are considered for the scrambled image. For evaluating the performance of the quantum image cryptography based on the three different chaotic maps, the NPCR, UACI, Entropy, SSIM, correlation characteristics and histogram analysis are determined. The attained NPCR, UACI, Entropy and SSIM of the CASIA2 dataset for Lorenz attractor are improved than the pixel permutation and Chen attractor. Thus, from the attained values, the Quantum Image Cryptography Based on Continuous Chaotic Map such as Lorenz attractor performs better for the statistical and differential analysis than the other chaotic maps.
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.
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.
In order to improve the security of traditional encryption systems, hyper-chaotic systems are introduced into the field of quantum image encryption. Firstly, the image is bitwise XOR by He fractional order hyper-chaotic Rabinovich system, and then the color image is represented as a quantum superposition state. The quantum image is scrambled by the unitary matrix generated by Logistic hyper-chaotic sequence, and then a hyper-chaotic sequence is generated to randomly replace the red, green and blue primary colors of each pixel to achieve the purpose of quantum image encryption. Finally, numerical simulation experiments are carried out on a computer. The experimental results show that the histogram of the encrypted image is flatter and even, the pixels are evenly distributed between 0 and 255, the correlation between adjacent pixels of the image is low. The average correlation coefficients of the red, green, and blue pixels of the encrypted image are 0.0012, 0.0025, and 0.0018. The system has high key sensitivity and can effectively resist statistical analysis attacks. The algorithm has good security and robustness.
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 recent years, in the context of the rapid development of quantum computing technology, quantum attack methods such as Shor’s algorithm pose a serious threat to the traditional public key encryption system based on number-theoretic puzzles. Using the characteristics of quantum bits, this paper proposes a quantum grey-scale image encryption method based on alternating quantum random walk. Firstly, the quantum representation model is used to transform the image into a quantum state, and then the quantum key is generated by the alternating quantum random walk algorithm, and combined with the quantum gate operation for encrypting the grey-scale image data, which not only inherits the advantage of the anti-attack of the quantum computation, but also, through the quantum parallelism and the non-clonability, which solves the security and efficiency bottleneck of traditional image encryption in the quantum era and significantly improves the security of grey-scale image encryption. The algorithm proposed in this paper has been verified by simulation experiments, and the experimental results show that the method is excellent in encryption and decryption effects, and for the encrypted image, a number of performance analyses have been carried out, and the analysis results show that the proposed encryption method has a high degree of security, and it can effectively resist the statistical attack, noise attack, etc., and the distribution of the histogram of encrypted image is more uniform, the pixel correlation analysis is close to 1, and the information entropy is close to 7.999.