Abstract As a fundamental form of information representation, image encryption is a significant research issue in the multimedia era. An image encryption scheme is proposed benefiting from chaotic random behavior characteristics of Boson sampling (BS) probability distribution, where the chaotic random number sequence is used to implement the encryption process including scrambling image pixels and altering the values of pixels. Further, a BS‐based image encryption prototype system is constructed on the programmable silicon photonic processor chip for BS with 5‐mode 2‐photon, which can encrypt 4 × 4 grayscale images. Besides, experiments for encrypting 256 × 256 gray‐scale images with 20‐mode 8‐photon BS are simulated on the StrawberryFields photonic quantum software platform. Numerical analyses demonstrate the proposed scheme has good effectiveness in terms of randomness test, information entropy, histogram, correlation, key space, key sensitivity, and anti‐attack, offering gains in many cryptographic applications. The BS‐based image encryption prototype system extends the application of BS to solve practical problems in addition to proving quantum advantages.
Abstract As a fundamental form of information representation, image encryption is a significant research issue in the multimedia era. An image encryption scheme is proposed benefiting from chaotic random behavior characteristics of Boson sampling (BS) probability distribution, where the chaotic random number sequence is used to implement the encryption process including scrambling image pixels and altering the values of pixels. Further, a BS‐based image encryption prototype system is constructed on the programmable silicon photonic processor chip for BS with 5‐mode 2‐photon, which can encrypt 4 × 4 grayscale images. Besides, experiments for encrypting 256 × 256 gray‐scale images with 20‐mode 8‐photon BS are simulated on the StrawberryFields photonic quantum software platform. Numerical analyses demonstrate the proposed scheme has good effectiveness in terms of randomness test, information entropy, histogram, correlation, key space, key sensitivity, and anti‐attack, offering gains in many cryptographic applications. The BS‐based image encryption prototype system extends the application of BS to solve practical problems in addition to proving quantum advantages.
Abstract Images are crucial for digital signal transmission and face significant security challenges due to the growing sophistication of cyber threats. Although classical cryptography based on logistic map is commonly used for image encryption, it is often susceptible to periodic and predictable behaviors arising from specific initial conditions and parameter settings. The predictability poses a risk to the security of encryption system. In response to the challenges, this paper presents a novel image cryptography scheme, as the logistic map image cryptography scheme based on chaotic quantum Boson sampling (LM‐BS), which combines the encryption strength of the logistic map with the inherent unpredictability of chaotic quantum Boson sampling(QBS). LM‐BS scheme takes advantage of the distinctive properties of random interference among bosons in quantum systems, significantly enhancing the sensitivity, randomness, and unpredictability of encryption keys, which effectively addresses the periodicity and predictability challenges associated with traditional chaotic systems. Moreover, the image encryption experiments are put on the silicon photonic chips and the StrawberryFields photonic platform by using LM‐BS scheme on various grey‐scale images. The experimental results indicate that the LM‐BS enables reliable image encryption and decryption, reduces the risk of key leakage, and successfully ensures the security and privacy of image transmission. Overall, the LM‐BS scheme lays a strong theoretical foundation for future encryption based on quantum computation and demonstrates the considerable potential for a wide range of applications.
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.
Abstract It is proven that Boson sampling is a much promising model of optical quantum computation, which is applied to designing quantum computer successfully, such as “Jiuzhang” . However, the meaningful randomness of Boson sampling results has not been utilized or exploited. In this research, Boson sampling is applied to design a quantum random number generator (QRNG) by fully exploiting the randomness of Boson sampling results, and its prototype system is constructed with the programmable silicon photonic processor, which can generate unbiased random sequences and overcome the shortcomings of the existing discrete QRNGs such as source‐restricted, high demand for the photon number resolution capability of detector and slow self‐detection generator speed. Boson sampling is implemented as a random entropy source, and random bit strings with satisfactory randomness and uniformity can be obtained after post‐processing the sampling results. It is the first approach for applying the randomness of Boson sampling results to develop a practical prototype system for actual tasks, and the experiment results demonstrate that the designed Boson sampling‐based QRNG prototype system passes 15 tests of the NIST SP 800‐22 statistical test component, which proves that Boson sampling has great potential for practical applications with desirable performance besides quantum advantage.
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.
In order to enhance the security of encrypted images, a new quantum image encryption algorithm is proposed. This algorithm combines Chen's hyper-chaotic system with Double-random Phase Encoding (DRPE). The pixel values of the original quantum image are diffused using DRPE, while the pixel positions are scrambled through Cyclic Translation (CT). The hyper-chaotic sequences generated by Chen's hyper-chaotic system control the scrambling and diffusion operations. Numerical simulations and theoretical analyses have shown that this algorithm is highly effective in resisting illegal attacks. The encrypted image generated by this algorithm exhibits lower pixel correlation and more evenly distributed histogram. Overall, the proposed algorithm represents a robust and secure approach for image encryption
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.