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.
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.
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.
To secure and protect the photos from unfair tactics, the encryption process is used. the advent of the digital era has made it exceedingly easy to hack any data kept on the cloud. Encryption is critical to ensuring communication security, which is a crucial issue. There are numerous photo encryption methods that mostly rely on chaotic logistic maps; however, they have downsides such a small key space and low security. Current analysis introduced experimental results of quantum chaotic cryptosystem,3D-Chaotic map and quantum chaotic logistic map. This paper we measure image encryption parameters are Entropy, structural similarity index measure, combined average changing intensity and net pixel change rate which defines utilization of suitable image encryption approaches. For the cypher and the original image, we quantify the correlation coefficient value in both the horizontal and vertical positions with comparison of all three existing Approach-es performance. The scientific and practical economic results reveal that the quantum chaotic cryptosystem has outstanding performance and in future with utilization of advanced Approaches we can resist various cryptographic attacks.
This research presents a novel hybrid image encryption system that combines quantum cryptography, chaos theory and reservoir computing to address the limitations of conventional encryption methods. With the rapid advancements in quantum computing, traditional systems like RSA, DHKE (related to prime number factorization) are vulnerable to quantum attacks i.e. Shor's algorithm, Grover's algorithm. In response, this study proposes a hybrid solution that uses quantum cryptographic protocols, particularly the E91 protocol, to generate secure, eavesdrop-proof keys through quantum entanglement. The integration of chaos theory, specifically the Lorenz hyper-chaotic system, enhances the encryption system by adding unpredictability and sensitivity to initial conditions, making it more resistant to both classical and quantum-based attacks. Reservoir computing is used to improve computational efficiency, enabling faster and more effective encryption and decryption processes. The system achieved encryption times as low as 0.0296s and decryption times as low as 0.0164s for 128x128 images, with MAE reduced for 300-600 node networks, and NPCR and UACI above 99.6% and 0.49, respectively, across various image sizes and configurations. By combining quantum cryptography, chaos theory and reservoir computing, this approach offers both enhanced security and practical feasibility for image encryption in the age of quantum computing.
Data, especially image data, is transmitted at an incredible rate due to the exponential growth in the number of connected devices brought about by the fast development of consumer electronics. Data transmission security remains fundamental in effective communication systems, especially with the emergence of the quantum era. Quantum advancements challenge traditional asymmetric cryptography, necessitating the requirement for new encryption schemes. The multimedia encryption schemes pose further challenges due to its large size, structural complexity, real-time requirements, and unique attack vectors specific to multimedia data. The current classical image encryption algorithms do not fully address the challenges posed by Quantum technology for securing the multimedia transmission. This paper proposes a hybrid framework combining Quantum Key Distribution (QKD), chaos-based encryption, and Post-Quantum Cryptography (PQC) to secure multimedia data, particularly images, in IoT consumer electronic networks. Integrating 2D-Logistic Sine Coupling Map (2D-LSCM), initialized with the Keys generated from QKD, and NTRU algorithm, this scheme achieves robust security and efficient performance. This new architecture improves processing speeds and enhances specificity and sensitivity values, fortifying chaotic map performance. Our experimental results and comprehensive security analysis demonstrate the security and performance of the framework. Correlation Analysis using Person correlation coefficient, with a nearing zero value, ensures the confidentiality of the encrypted image.
Secure image transmission is increasingly vital in the digital era, especially against emerging quantum threats. This study proposes a hybrid image encryption scheme that integrates Quantum Key Distribution (QKD) using the BB84 protocol with a combination of 7-dimensional (7D) and 2-dimensional (2D) hyperchaotic systems to achieve robust security. The BB84 protocol facilitates quantum-assisted key exchange, ensuring resistance to eavesdropping, while the hyperchaotic systems provide high entropy and complex randomness, utilized in a layered permutation-substitution encryption framework. The initial seeds for chaotic sequences are derived using a SHA-512 hash of both the input image and quantum-generated key, ensuring uniqueness and sensitivity. Experimental validation was conducted using several benchmark images. The information entropy values of the ciphered images reached up to 7.9993, indicating excellent randomness. Differential analysis showed high resistance to small perturbations, with NPCR exceeding 99.61% and UACI averaging around 33.47%, which meet standard security thresholds. Histogram and chi-square tests confirmed the uniform pixel distribution, with chi-square values below 280, satisfying the randomness criterion for 8-bit images. Furthermore, correlation coefficients of adjacent pixels dropped to near zero, evidencing effective decorrelation. The encryption scheme also demonstrated robustness to data loss, as shown by the successful decryption of partially corrupted cipher images. Robustness testing under partial data loss (200×200-pixel blocks) also demonstrated visual recoverability and algorithm resilience. Overall, the proposed BB84-assisted dual-hyperchaotic encryption scheme offers a secure and computationally effective solution for protecting sensitive image data, making it suitable for post-quantum secure communications.
The proposed work delves into the utilization of chaotic maps along with the quantum mechanisms to strengthen the security of the digital images along with addressing the limitations posed by conventional 1-D chaotic systems characterized by their pseudorandom and periodic attributes. Leveraging the inherent uncertainty in quantum theory, the proposed research introduces a new image encryption scheme. This method is built upon the concepts of two-dimensional quantum coding and the 1-D sine-based chaotic map (1-D SBCM). In the proposed encryption scheme, initially, a random sequence is created using 1-D SBCM by varying the seed parameters. This sequence is subsequently utilized for the purpose of scrambling. After that, a pseudorandom number generator (PRNG) is meticulously devised, drawing inspiration from the concepts of quantum coherence. This PRNG generates a confidential code stream that defies predictability and remains incongruent with the plaintext image, thereby contributing to heightened security levels. Subsequently, the research employs the novel enhanced quantum representation (NEQR) model, capitalizing on its advanced capabilities. Within this framework, the study introduces a quantum right cyclic shift operator, as well as a quantum XOR operator. These operators play a vital role in the formation of highly robust encrypted images. The application of these quantum operators not only enhances the security measures but also increases the complexity of the encryption procedure Statistical evidence derived from comprehensive experimentation corroborates the efficacy of the proposed image encryption scheme. Through rigorous analysis, it becomes evident that the system exhibits a robust performance in terms of strong security. The integration of quantum principles and quantum coding demonstrates that the proposed encryption scheme is resilient against potential threats.