In IoT networks and systems, the security of digital image data is a critical concern, which becomes even more critical in the post-quantum era where traditional encryption schemes will be vulnerable and can be easily compromised. This paper introduces a gate-efficient Quantum Image Encryption scheme that comprises pre-encryption quantum compression and chaos-based qubit encryption. By simplifying the quantum circuits that encode classical images into their quantum representations, the proposed scheme reduces the total number of quantum gates required before the actual encryption begins. This results in a more gate-efficient encryption pipeline for resource-constrained IoT systems. The encryption scheme comprises a quantum compression stage—by employing Boolean expression minimization— to simplify the quantum circuits in image preparation phase, followed by a two-stage encryption mechanism that employs quantum cellular automata and chaos-based qubit transformations. Extensive evaluation against key security parameters demonstrates close-to-ideal results for information entropy, and correlation analysis. The scheme also exhibits strong resilience against differential attacks, proving its effectiveness in securing image data for IoT devices in post-quantum environments.
In IoT networks and systems, the security of digital image data is a critical concern, which becomes even more critical in the post-quantum era where traditional encryption schemes will be vulnerable and can be easily compromised. This paper introduces a gate-efficient Quantum Image Encryption scheme that comprises pre-encryption quantum compression and chaos-based qubit encryption. By simplifying the quantum circuits that encode classical images into their quantum representations, the proposed scheme reduces the total number of quantum gates required before the actual encryption begins. This results in a more gate-efficient encryption pipeline for resource-constrained IoT systems. The encryption scheme comprises a quantum compression stage—by employing Boolean expression minimization— to simplify the quantum circuits in image preparation phase, followed by a two-stage encryption mechanism that employs quantum cellular automata and chaos-based qubit transformations. Extensive evaluation against key security parameters demonstrates close-to-ideal results for information entropy, and correlation analysis. The scheme also exhibits strong resilience against differential attacks, proving its effectiveness in securing image data for IoT devices in post-quantum environments.
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.
Cryptography plays an important role in ensuring data security and authentication within information processing systems. As the prevalence of digital imagery continues to grow, safeguarding this form of data becomes increasingly crucial. However, existing security protocols, reliant on complex mathematical models, exhibit vulnerabilities in effectively protecting information from both internal and external threats. Moreover, the forthcoming advent of quantum computing poses a significant challenge, as it could decrypt data encrypted by classical. In this paper, we propose an efficient implementation scheme for a quantum image encryption algorithm combining the generalized affine transform and logistic map. We evaluated developed quantum circuits using qiskit and quantum devices to validate the encryption technique. Through comprehensive performance analysis, we have demonstrated the efficiency of the chosen encryption algorithm across various criteria. Furthermore, we introduce a hybrid methodology aimed at mitigating circuit complexity and reducing quantum cost. Leveraging the Espresso algorithm and incorporating an ancilla qubit into the circuitry, we achieve a remarkable 50\% reduction in cost while maintaining security and efficiency. Finally, we conducted robustness and security analyses to assess the resilience of our encryption method against diverse noise attacks. The results confirm that our proposed quantum image encryption technique provides a secure solution and offers precise and measurable quantum image processing capabilities.
The rapid advancement in consumer technology has led to an exponential increase in the connected devices, resulting in an enormous and continuous flow of data, particularly the image data. This data needs to be processed, managed, and secured efficiently, especially in the quantum-enabled consumer technology era. This paper, in this regards, presents a quantum image encryption scheme featuring a novel two-phase chaotic confusion-diffusion architecture. The proposed architecture consists of four distinct confusion-diffusion modules that perform a simultaneous qubit and pixel-level encryption on both the position and intensity of quantum encoded pixels. Moreover, quantum circuits for′qubit-level chaotic transformation′and′chaos-based selective perfect shuffle operation′have been implemented, which collectively enhance the encryption strength of the proposed scheme. Extensive evaluation has been performed based on various statistical security parameters, such as entropy and correlation. When subjected to differential attacks, the proposed scheme proved its resilience exhibiting ideal results of average 99.6% NPCR (Number of Pixels Change Rate) and 33.5% UACI (Unified Average Changing Intensity). Besides, the proposed scheme also demonstrated resilience against occlusion attacks. Tests involving 50% data occlusion from encrypted images validated the proposed scheme’s capability to successfully decrypt the tampered images, recovering maximum information.
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.
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.
The advent of quantum computers could enable the resolution of complex computational problems that conventional cryptographic protocols find challenging. As a result, the formidable computing capabilities of quantum computers may render all present-day cryptographic schemes that rely on computational complexity ineffectual. Inspired by these possibilities, the primary purpose of this paper is to suggest a quantum image encryption scheme based on quantum cellular automata with mixed multi-chaos hybrid maps and a hyperchaotic system with quantum operations. To achieve desirable encryption outcomes, we designed an encryption scheme involving two main operations: (1) pixel-level diffusion and (2) pixel-level permutation. Initially, the secret keys generated using the hyperchaotic system were closely tied to the original image. During the first phase, the establishment of correlations among the image pixels, in addition to the three chaotic sequences obtained from the hyperchaotic system, was achieved with the application of a quantum-state superposition and measurement principle, wherein the color information of a pixel is described using a single qubit. Therefore, the three channels of the plain image were subjected to quantum operations, which involve Hadamard transformation and the quantum-controlled NOT gate, before the diffusion of each color channel with the hyperchaotic system. Subsequently, a quantum ternary Toffoli gate was used to perform the diffusion operation. Next, the appropriate measurement was performed on the three diffused channels. To attain the confusion phase, a blend of mixed multi-chaos hybrid maps and a two-dimensional quantum cellular automaton was used to produce random and chaotic sequence keys. Subsequently, the circular shift was utilized to additionally shuffle the rows and columns of the three diffused components, in order to alter the positions of their pixel values, which significantly contributes to the permutation process. Lastly, the three encoding channels, R, G, and B, were merged to acquire the encrypted image. The experimental findings and security analyses established that the designed quantum image encryption scheme possesses excellent encryption efficiency, a high degree of security, and the ability to effectively withstand a diverse variety of statistical attacks.