Quantum computing introduces major threats to conventional image encryption methods, especially in medical contexts. This paper addresses these threats by developing a quantum-resistant encryption scheme for medical images. We present a novel framework combining: (1) a novel Mixed Logistic-Ikeda-Henon (MLIH) chaotic map for pseudorandom key generation, (2) quantum image representation using the Novel Enhanced Quantum Representation (NEQR) model, and (3) a two-stage encryption process employing Controlled-Not (CNOT) gate chaining for diffusion and One-Time Pad (OTP) with MLIH-generated keys for confusion. The RGB channels are processed separately through quantum state conversion, CNOT-based diffusion, and keyed confusion before final recombination. To validate practical feasibility, the proposed encryption scheme was implemented on IBM’s 127-qubit ibm_sherbrooke quantum processor, demonstrating real-world feasibility. Experimental validation shows near-ideal entropy (7.9977), superior NPCR (99.97%) and UACI (33.89%) values, and an expansive key space (2 1952 ). The novel MLIH demonstrates a 12.7% improvement in logic gate efficiency compared to conventional chaotic and the image encryption has quantum advantage through parallel CNOT operations. The hardware execution yielded a throughput of 4,500 Circuit Layer Operations Per Second (CLOPS), indicating efficient real-time performance on NISQ devices, Moreover, the echoed cross-resonance (ECR) gate error remained within a median of 1.1 × 10⁻ 2 , supporting reliable circuit execution. The proposed scheme outperforms contemporary quantum and classical encryption approaches in terms of entropy, NPCR, UACI, and key sensitivity, all while maintaining a computational complexity of O(n), ensuring scalability. This study effectively bridges the gap between theoretical quantum security models and real-world implementation on existing NISQ devices, demonstrating resilience against classical statistical and differential attacks, as well as quantum-specific threats such as Grover’s brute-force search and quantum chosen-plaintext attacks. The successful deployment of IBM quantum hardware positions this scheme as a viable solution for secure medical image transmission in quantum-era healthcare systems.
Quantum computing introduces major threats to conventional image encryption methods, especially in medical contexts. This paper addresses these threats by developing a quantum-resistant encryption scheme for medical images. We present a novel framework combining: (1) a novel Mixed Logistic-Ikeda-Henon (MLIH) chaotic map for pseudorandom key generation, (2) quantum image representation using the Novel Enhanced Quantum Representation (NEQR) model, and (3) a two-stage encryption process employing Controlled-Not (CNOT) gate chaining for diffusion and One-Time Pad (OTP) with MLIH-generated keys for confusion. The RGB channels are processed separately through quantum state conversion, CNOT-based diffusion, and keyed confusion before final recombination. To validate practical feasibility, the proposed encryption scheme was implemented on IBM’s 127-qubit ibm_sherbrooke quantum processor, demonstrating real-world feasibility. Experimental validation shows near-ideal entropy (7.9977), superior NPCR (99.97%) and UACI (33.89%) values, and an expansive key space (2 1952 ). The novel MLIH demonstrates a 12.7% improvement in logic gate efficiency compared to conventional chaotic and the image encryption has quantum advantage through parallel CNOT operations. The hardware execution yielded a throughput of 4,500 Circuit Layer Operations Per Second (CLOPS), indicating efficient real-time performance on NISQ devices, Moreover, the echoed cross-resonance (ECR) gate error remained within a median of 1.1 × 10⁻ 2 , supporting reliable circuit execution. The proposed scheme outperforms contemporary quantum and classical encryption approaches in terms of entropy, NPCR, UACI, and key sensitivity, all while maintaining a computational complexity of O(n), ensuring scalability. This study effectively bridges the gap between theoretical quantum security models and real-world implementation on existing NISQ devices, demonstrating resilience against classical statistical and differential attacks, as well as quantum-specific threats such as Grover’s brute-force search and quantum chosen-plaintext attacks. The successful deployment of IBM quantum hardware positions this scheme as a viable solution for secure medical image transmission in quantum-era healthcare systems.
In the age of digital technology, medical images play an important role in the healthcare industry, which aids surgeons in making precise decisions and reducing the diagnosis time. However, the storage of large amounts of these images in third-party cloud services raises privacy and security concerns. There are a lot of classical security mechanisms to protect them. Although, the advent of quantum computing entails the development of quantum-based encryption models for healthcare. There is a significant demand for resource-efficient, quantum-secure image encryption mechanisms that leverage existing classical infrastructure. Hence, in this paper, a novel quantum chaos-based encryption scheme for medical images has been introduced. The model utilizes bit-plane scrambling, a 3D quantum logistic map, quantum operations in the diffusion phase, a hybrid chaotic map, and DNA encoding in the confusion phase to transform the plain medical image into a cipher medical image. The proposed scheme has been evaluated using multiple statistical analyses and validated against more attacks such as differential attacks, known and chosen plaintext attacks with three different medical datasets, and theoretically, as well. Hence, the introduced encryption model has proved to be more attack-resistant and robust than other existing image encryption schemes, ensuring the secure storage of medical images in cloud environments.
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.
Safeguarding image confidentiality is a crucial communication concern due to the valuable information that must remain inaccessible to unauthorized users. However, the imminent emergence of quantum computers has introduced pressing security concerns to current cryptography. This paper proposes a quantum-resistant cryptosystem integrating a three-qubit entanglement-based Quantum Key Distribution protocol with a chaotic Henon map to develop an image transmission system resilient to classical and quantum adversaries. This QKD employs bidirectional qubit transmission to entangle three qubits, resulting in a quantum-secured key that is double that of the E91 protocol and demonstrates exceptional eavesdropper detection capabilities via the CHSH inequality violation. A 2D Henon map is utilized to address the intrinsic vulnerabilities related to key size and security in one-dimensional logistic maps. The expanded key generates a more complex sequence employing the Henon map, ensuring the utmost security of the encryption by integrating the chaotic randomness with the cryptographic properties embedded in entanglement. The findings from various security assessments indicate that the proposed encryption is both reliable and effective. It exhibits robust resistance to differential analysis, showing NPCR at 99.6% and UACI near 50%. A colossal 10220 key space thwarts brute-force attempts, while near-zero correlation and uniform pixel-intensity distribution confirm strong statistical security, highlighting the advantages of quantum–classical cryptography protocols.
Medical image security is crucial for patient confidentiality because it is exposed to many attacks, such as editing photos or moving the affected part to another place, and others. Encryption is an efficient technique to protect the confidentiality of images, but traditional encryption suffers from brute-force attacks. This research proposes an encryption method depending on quantum concepts to resist brute-force attacks using a 3D logistic map to generate keys; the keys were scrambled to increase the randomness, and using the best image scrambling scheme generated by a genetic algorithm as a first stage to increase the strength of the encryption algorithm. The quantum scrambled image is then encrypted by using XOR process depending on a 3D logistic map key generator. The proposed encrypting and decrypting algorithm utilize a NEQR quantum image representation. Numerical and simulation analyses using MATLAB demonstrate that the suggested encryption algorithm is robust, realizable, and highly efficient in comparison to its classical equivalent.
Abstract Ensuring the security and privacy of patient data in e‐healthcare systems that rely on cloud computation is of utmost importance. Traditional encryption is no longer resistant to quantum attacks and safeguards sensitive medical images. To tackle this issue, robust security countermeasures are proposed by integrating quantum encryption with a cloud‐based healthcare system. The encryption scheme utilizes the Generalized Novel Enhancement Quantum Representation (GNEQR) and the Novel Enhancement Quantum Representation (NEQR) to provide a framework for representing color and grayscale healthcare images. The proposed quantum algorithm uses quantum logic for image scrambling, which is combined with the encryption key by the Xor quantum gate. The encryption key is generated by 9D chaotic and permutated before encryption. Finally, channel re‐ordering is applied for color images. The simulation results for 15 medical tests with an encryption key space >2600 on a developed e‐healthcare system demonstrate the effectiveness and reliability of the proposed work where the average number of pixels change rates was 99.82, while the unified average change intensity rate was 33.51, entropy was 7.9, the horizontal, vertical, and diagonal correlation coefficients averaged 0.000533333, 0.000706667, and 0.00076, respectively. Finally, the mean squared error (MSE) between the original and encrypted images was 10203.72. These findings improve digital healthcare by revealing the solutions' performance, security, and efficacy.
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.