Quantum key distribution (QKD) is a viable technique for safeguarding image transmission against numerous attacks. To address the limitations of existing methods in securing electronic medical records, we have explored an encryption technique using a set of real-time medical images along with existing standard images using QKD protocols including BB84 (Bennett-Brassard 1984), CASCADE (Cascading Error Correction Algorithm for Data Exchange), and differential-phase-shift (DPS) under the fiber-based (OFC) and free-space (FSO) channels. It utilizes the quantum bit-plane representation of the Real Ket (QBRK) model and a logistic chaotic system with XOR operation. The performance of the developed framework is tested via visual illustration and 11 different quantitative assessments. The average entropy of the scrambled image for the medical source image is 7.9896, which is quite near to the optimum value of 8. TheUACI(Unified Averaged Changed Intensity) and theNPCR(Number of Pixels Change Rate) metrics values lie between 33.7879 to 33.9711 and 99.6014 to 99.8000 for the FSO channel. The BB84 QKD protocol achieves a QBER (Quantum Bit Error Rate) of 0.0028 for an FSO channel with DCR (Dark Count Rate), which improves to 0.0012 when DCR is ignored for a 10 km link range. In addition, we analyzed and compared the effect of OFC on system output as the quantum channel. From several experiments, it is observed that the BB84 provides better results against CASCADE and DPS. The proposed work is validated using the Optisystem 15.1 software under FSO and for OFC.
Quantum key distribution (QKD) is a viable technique for safeguarding image transmission against numerous attacks. To address the limitations of existing methods in securing electronic medical records, we have explored an encryption technique using a set of real-time medical images along with existing standard images using QKD protocols including BB84 (Bennett-Brassard 1984), CASCADE (Cascading Error Correction Algorithm for Data Exchange), and differential-phase-shift (DPS) under the fiber-based (OFC) and free-space (FSO) channels. It utilizes the quantum bit-plane representation of the Real Ket (QBRK) model and a logistic chaotic system with XOR operation. The performance of the developed framework is tested via visual illustration and 11 different quantitative assessments. The average entropy of the scrambled image for the medical source image is 7.9896, which is quite near to the optimum value of 8. TheUACI(Unified Averaged Changed Intensity) and theNPCR(Number of Pixels Change Rate) metrics values lie between 33.7879 to 33.9711 and 99.6014 to 99.8000 for the FSO channel. The BB84 QKD protocol achieves a QBER (Quantum Bit Error Rate) of 0.0028 for an FSO channel with DCR (Dark Count Rate), which improves to 0.0012 when DCR is ignored for a 10 km link range. In addition, we analyzed and compared the effect of OFC on system output as the quantum channel. From several experiments, it is observed that the BB84 provides better results against CASCADE and DPS. The proposed work is validated using the Optisystem 15.1 software under FSO and for OFC.
ABSTRACT The rapid development of healthcare system has increased the necessities for the secure medical image transmission. As quantum computers develop, classical cryptographic techniques become vulnerable to quantum attacks. This paper proposes QKD assisted quantum encryption for medical images. BB84 protocol is utilised to generate a secure shared key, which is further enhanced using Henon maps. The logistic map whose parameters are derived from the shared key is employed to generate the permutation sequence for pixel values. Medical images are encoded using the novel enhanced quantum representation (NEQR) and encrypted via quantum permutation and quantum XOR operations employing block‐wise strategy. The proposed method was evaluated in both ideal and noisy quantum environments such as amplitude damping, depolarising, bit‐flip and phase damping noise models. The experimental results show strong security performance on a benchmark and medical images with high entropy values, near zero‐pixel correlation and resistance to differential attacks. Additionally, noise analysis shows that bit‐flip and amplitude damping noises affect the image reconstruction more than phase damping and depolarising noise. Overall, the proposed framework provides a secure solution for medical image security.
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.
Secure remote sharing of medical images is essential for advancing telemedicine, accurate diagnostics, and collaborative healthcare delivery. The traditional cryptography techniques are fast turning to be susceptible to quantum computing risks and generally are less efficient in high throughput medical settings. To counter such a shortcoming, we present an innovative quantum-oriented solution that utilizes optimized methods of secure and real-time medical image transmission over a long-distance network. In this method, Quantum Key Distribution (BB84 protocol), hybrid cryptography, quantum informed optimization, and quantum steganography are used to provide efficient high-fidelity and low latency transmission of images. The QKD is used to securely create symmetric keys that are to be used in the AES 256 encryption of the image and Elliptic Curve Cryptography is applied so that the metadata can be kept confidential. Immutable and transparent access logs are kept by using the blockchain technology. In order to even improve the performance, a dynamically tuning encryption parameters using a Quantum Genetic Algorithm can be applied to eliminate the computing overhead. Experimental testing with NIH Chest X-ray dataset shows an average encryption and decryption speed of 38.1 milliseconds, with a success rate of more than 25% relative to the conventional post-quantum cryptographic system. The results of a secure transmission show a decrease in latency of 12.5% over the TLS-enhanced QKD. The system keeps the Quantum Bit Error Rate at less than 5% under realistic noise levels and retains more than 75% of the key material obtained. In quantum steganography, the level of accuracy to detect tampering is 98.6%, hence data integrity. The solution has shown the capability to integrate quantum-level security, computing performance, and regulatory durability to become a trusted and long-term process of safe sharing of medical images in modern healthcare systems.
Ensuring patient secrecy and maintaining data integrity are critical in healthcare information security. With increasing demands for stronger protection in the management and storage of medical images, this study introduces an innovative framework utilizing chaos-based quantum encryption for enhanced security. This approach combines a DNA codec with the QFBT (Quantum Fibonacci Transform), creating a unique dual-encryption method for quantum color images. The process begins with converting a standard color image to quantum data through GQIR (Generalized Quantum Image Representation) technique. A DNA codec then encodes and decodes the pixel color data of the quantum image, achieving pixel-level diffusion. Finally, the QFBT is applied to scramble the image's spatial data. The resulting transformed image is then used as the key matrix in quantum XOR functions. Findings from the experiment indicate that both the correlation and peak value of the encrypted image histograms show strong similarity. The mean NPCR (Normalized Pixel Change Rate) for the RGB channels is 99.63%, while UACI (Uniform Average Change Intensity) is 33.43%. Additionally, the mean information entropy is approximately 7.9992. These findings demonstrate the effectiveness of QDIES in providing robust security for medical image data.
This research proposes a combination of Quantum Key Distribution (QKD) based on the BB84 protocol with Improved Logistic Map (ILM) to improve data transmission security. This method integrates quantum key formation from BB84 with ILM encryption. This combination creates an additional layer of security, where by default, the operation on BB84 is only XOR-substitution, with the addition of ILM creating a permutation operation on quantum keys. Experiments are measured with several quantum measurements such as Quantum Bit Error Rate (QBER), Polarization Error Rate (PER), Quantum Fidelity (QF), Eavesdropping Detection (ED), and Entanglement-based detection (EDB), as well as classical cryptographic analysis such as Bit Error Ratio (BER), Entropy, Histogram Analysis, and Normalized Pixel Change Rate (NPCR) and Unified Average Changing Intensity (UACI). As a result, the proposed method obtained satisfactory results, especially perfect QF and BER, and EBD, which reached 0.999.
With the growing demand for highly secure medical data transmission, this research introduces a fused cryptography framework that integrates mathematical quantum computing operations with advanced classical encryption techniques. The proposed method incorporates quantum principles, including quantum walks, quantum-based cyclic shift operators, quantum XOR operations, and quantum key image generation with classical methods such as bit-plane extraction and hyperchaotic system-based scrambling. A hyperchaotic map generates random key sequences to produce both a spatial domain random image and a quantum key image. The medical image is first decomposed into eight bit-planes, and only the high-information bit-planes (HIBPs) undergo encryption to optimize computational efficiency. HIBPs are scrambled using multilayer, block-wise, and diagonal permutations based on the chaotic sequences. Quantum encryption is then applied, starting with novel enhanced quantum representation encoding, followed by Baker map-based scrambling and quantum XOR diffusion to secure the final ciphertext. Extensive experiments, including entropy evaluation, noise attack resilience, clipping attack robustness, and correlation analysis, confirm the superior security and performance of the proposed method. Notably, the algorithm achieves near-ideal results, such as an entropy of 7.9999, a correlation coefficient of 0.0001, 98% plaintext recovery after 30% noise corruption, and 96% recovery after 25% ciphertext clipping, demonstrating its robustness for secure medical data transmission.