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.
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.
The emergence of quantum computing has introduced unprecedented security challenges to conventional cryptographic systems, particularly in the domain of optical communications. This research addresses these challenges by innovatively combining quantum key distribution (QKD), specifically the E91 protocol, with logistic chaotic maps to establish a secure image transmission scheme. Our approach utilizes the unpredictability of chaotic systems alongside the robust security mechanisms inherent in quantum entanglement. The scheme is further fortified with an eavesdropping detection mechanism based on CHSH inequality, thereby enhancing its resilience against unauthorized access. Through quantitative simulations, we demonstrate the effectiveness of this scheme in encrypting images, achieving high entropy and sensitivity to the original images. The results indicate a significant improvement in encryption and decryption efficiency, showcasing the potential of the scheme as a viable solution against the vulnerabilities posed by quantum computing advancements. Our research offers a novel perspective in secure optical communications, blending the principles of chaos theory with QKD to create a more robust cryptographic framework.
Quantum computing poses an unparalleled threat to the conventional methodologies of image encryption through its capability for mathematical-based security breaking. This paper discusses the integration of chaos theory with quantum mechanics in the development of robust algorithms for image encryption, considering the inherent vulnerabilities of classical approaches. We start with the basics of chaos theory and its implications in cryptography, emphasizing sensitivity regarding initial conditions and the unpredictability of chaotic systems. Then, we reviewed some of the existing quantum image encryption techniques and their limitations. Our analysis elucidates the potential of chaos-driven quantum algorithms for key generation and image scrambling to enhance security metrics such as key sensitivity, entropy, and unpredictability. We further discuss the performance of such algorithms in resistance against different attack vectors and their application domains, including healthcare, military, and digital rights management. The paper concludes by pointing out the directions of future research, hence calling for further development of sophisticated chaotic maps to integrate them into practical quantum image encryption solutions. The study points out that chaos-based quantum image encryption has strong potential to defend against evolving cyber threats.
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.
Quantum security improves cryptographic protocols by applying quantum mechanics principles, assuring resistance to both quantum and conventional computer attacks. This work addresses these issues by integrating Quantum Key Distribution (QKD) utilizing the E91 method with Multi-Layer Chaotic Encryption, which employs a variety of patterns to detect eavesdropping, resulting in a highly secure image-transmission architecture. The method leverages entropy calculations to determine the unpredictability and integrity of encrypted and decrypted pictures, guaranteeing strong security. Extensive statistical scenarios illustrate the framework's effectiveness in image encryption while preserving high entropy and sensitivity to the original visuals. The findings indicate significant improvement in encryption and decryption performance, demonstrating the framework's potential as a robust response to weaknesses introduced by advances in quantum computing. Several metrics, such as Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index (SSIM), Normalized Cross-Correlation (NCC), Bit Error Rate (BER), entropy values for original, encrypted, and decrypted images, and the correlation between original and decrypted images, validate the framework's effectiveness. The combination of QKD with Multi-Layer Chaotic Encryption provides a scalable and resilient technique to secure image communication. As quantum computing advances, this framework offers a future-proof approach for defining secure communication protocols in crucial sectors such as medical treatment, forensic computing, and national security, where information confidentiality is valuable.
The rapid growth in the storage and transmission of visual data across communication, sensing, and decision-making systems requires image encryption methods that are both computationally efficient and resilient against quantum-enabled adversaries. Classical chaotic encryption offers desirable properties such as sensitivity, unpredictability, and large key spaces, but its practical use is limited by restricted chaotic ranges, and conventional confusion–diffusion mechanisms often fail to eliminate structural redundancies in images. This thesis furthers the field by developing novel chaotic and gate-efficient quantum image encryption architectures. First, it introduces a new cosine-modulated polynomial chaotic map and validates its dynamical and statistical suitability for cryptographic key generation. Second, it designs lightweight yet effective chaotic primitives, including the Single-Round Single S-Box (SRSS) confusion mechanism and the featureaware diffusion scheme (PermutEx) that address the limitations in breaking correlation and maintaining efficiency. Third, these components are integrated into a complete endto- end chaos-based encryption framework that combines feature-driven segmentation, adaptive permutation, and dynamic confusion, demonstrating strong security across entropy, correlation, and differential metrics. Finally, the thesis advances two quantum image encryption architectures, i.e., a chaos-enhanced quantum image encryption framework that strengthens quantum confusion and diffusion mechanisms, and a gate-efficient architecture that reduces circuit depth and multi-qubit operations while retaining robust security. The proposed architectures achieve improved computational efficiency compared to existing chaos-based and quantum image encryption techniques, by reducing redundant operations, minimising circuit depth, and enabling lightweight yet effective confusion-diffusion processes. Consequently, this thesis provides a way forward for advancing image encryption by integrating chaotic and quantum approaches, offering practical steps for protecting visual data in the post-quantum era.
ABSTRACT The emergence of quantum computing has introduced unprecedented security challenges to conventional cryptographic systems, particularly in the domain of classical communications. Our research addresses these challenges by creatively combining quantum key distribution (QKD), specifically the E91 protocol, with logistic chaotic maps to establish a secure image transmission scheme. Our approach utilises the pseudo‐randomness of chaotic systems alongside the security mechanisms inherent in quantum entanglement‐based protocols. This framework leverages the E91 protocol for secure quantum key distribution to generate identical key pairs at both ends, followed by chaos encryption using the key as a basis for the parameters. This framework utilises the E91 protocol for secure quantum key distribution, leveraging maximally entangled pairs and CHSH inequality tests to detect eavesdropping and potential double‐agent attacks by identifying nonentangled qubits, therefore maintaining key confidentiality. Furthermore, through quantitative simulations, we demonstrate the effectiveness of this scheme through key space and key sensitivity analysis, histogram analysis, information entropy analysis, execution time analysis, and differential attack analysis in end‐to‐end encryption. The results indicate a significant improvement in encryption and decryption efficiency, showcasing the scheme's potential as a viable solution against the vulnerabilities posed by quantum computing advancements. Our research offers a novel perspective on a critical aspect of cybersecurity applications across healthcare, defence, finance, and beyond in the realm of secure quantum communication.