The development of blockchain technology has had far-reaching effects, notably on environmental monitoring, by radically altering the nature of decentralized processing and data integrity. Traditional blockchains, on the other hand, have problems with security, energy efficiency, and scalability. This study introduces QHealth- a smart healthcare consensus method for Quantum Entangled Medical Record (EQMR) Protocol which is part of our research work QUMA: Quantum Unified Medical Architecture using Blockchain. QHealth makes use of entanglement principles and verified quantum random numbers. Based on real-time sensor data from M-IoT sensors, QHealth simulated a blockchain network with 5 to 50 nodes, improving transaction throughput, consensus time, and energy efficiency. The study took into account things like data size, ambient noise, and network latency. Due to factors such as network size and data complexity, performance showed a nonlinear relationship with node count. Energy usage showed a non-linear growth with the number of nodes, although consensus time climbed logarithmically. When it comes to smart health and other conscious uses of blockchain technology, QHealth represents a positive step forward. It improves energy efficiency, transaction processing, decentralization, and security by using quantum entanglement. The study lays the groundwork for effective and sustainable environmental monitoring using blockchain, which has far-reaching consequences.
The development of blockchain technology has had far-reaching effects, notably on environmental monitoring, by radically altering the nature of decentralized processing and data integrity. Traditional blockchains, on the other hand, have problems with security, energy efficiency, and scalability. This study introduces QHealth- a smart healthcare consensus method for Quantum Entangled Medical Record (EQMR) Protocol which is part of our research work QUMA: Quantum Unified Medical Architecture using Blockchain. QHealth makes use of entanglement principles and verified quantum random numbers. Based on real-time sensor data from M-IoT sensors, QHealth simulated a blockchain network with 5 to 50 nodes, improving transaction throughput, consensus time, and energy efficiency. The study took into account things like data size, ambient noise, and network latency. Due to factors such as network size and data complexity, performance showed a nonlinear relationship with node count. Energy usage showed a non-linear growth with the number of nodes, although consensus time climbed logarithmically. When it comes to smart health and other conscious uses of blockchain technology, QHealth represents a positive step forward. It improves energy efficiency, transaction processing, decentralization, and security by using quantum entanglement. The study lays the groundwork for effective and sustainable environmental monitoring using blockchain, which has far-reaching consequences.
A substantial spike in the need for quality healthcare has resulted from people being more cognizant of health issues. With blockchain, healthcare providers may safely share patient information electronically, which is especially important given the sensitive nature of the data contained inside them. However, flaws in the current blockchain design have surfaced since the dawn of quantum computing systems. The study proposes a novel quantum inspired blockchain system (Qchain) and constructs a unique entangled quantum medical record (EQMR)system with an emphasis on privacy and security. This Qchain relies on entangled states to connect its blocks. Automated production of the chronology indicator reduces storage capacity requirements by connecting entangled BloQ (blocks with quantum properties) with controlled activities. One qubit is used to store the hash value of each block. A lot of information regarding quantum internet is included in the protocol for the entangled quantum medical record (EQMR). EQMR can be accessed in Medical Internet of Things (M-IoT) systems may be kept private and secure, and their where-abouts can be monitored in the event of an emergency. The protocol also uses quantum authentication in place of more conventional methods like encryption and digital signatures. Mathematical research shows that the quantum converged blockchain (QCB) is highly safe against attacks such as the External attack, Intercept-Measure-Repeat attack, and Entanglement-Measure attack. The reliability and auditability evaluations of the entangled BloQ, as well as the quantum circuit design for computing the hash value, are presented. There's also a comparison between the suggested approach and several other quantum blockchain designs.
Background and Aims: Rising quantum hazards and flaws in conventional encryption make cloud-based healthcare data security harder. Quantum-Secure HealthChain, a new architecture using blockchain and quantum computing, improves medical data security, patient privacy, and data fidelity. Methods: To prevent quantum attacks, the proposed system uses Quantum Key Distribution (QKD) for safe cryptographic key exchange and quantum-resistant encryption. Blockchain technology secures medical records, while multi-layered encryption ensures data privacy. Quantum Biometric Authentication improves access control using quantum entanglement and biometric data. Key generation, encryption, blockchain storage, authentication, and decryption are system process steps. Experimental evaluation focuses on encryption speed, resource economy, throughput, and scalability using simulated healthcare data. Results: Experimental data demonstrate system strength and efficiency. Encryption and decryption perform consistently for 1 to 100 MB data sizes with negligible overhead. Throughput can reach 105 transactions per second under normal demand; CPU (82%) and memory (210 MB) utilization are low. Scalability studies show linear expansion lets the system handle increased data volumes and user demands without sacrificing performance. Security study confirms quantum attack, data corruption, and unauthorized access resistance. Conclusion: Quantum-Secure HealthChain offers a revolutionary method to cloud-based healthcare system security. Blockchain-quantum computing integration ensures strong authentication, safe key exchange, and quantum-resistant encryption. Its security, scalability, and efficiency make it a future-ready platform for safe medical data management, reducing quantum computing hazards.
Using blockchain technology and quantum computing together is a burgeoning area of research that has the potential to revolutionize data storage and processing. Although blockchain technology has already significantly advanced in decentralized data storage and secure transactions, traditional computing methods must improve speed, scalability, and security. However, with the development of quantum computing, these limitations may soon be outdated. By leveraging optimization algorithms, quantum computing can accelerate the mining of new blocks on the blockchain. This, in turn, can improve the overall performance of blockchain networks and enable more efficient transactions. Furthermore, quantum computing can strengthen blockchain security by enhancing cryptographic protocols and preventing attacks on the network. Additionally, quantum computing can optimize complex mathematical calculations necessary for blockchain applications. In this paper, we will explore the various potential applications of the quantum blockchain technology in healthcare, and the current state of research and development in this field. In addition, we will discuss the challenges that must be overcome to utilize this technology fully. We aim to stimulate further research and innovation in this emerging field by shedding more light on it.
Blockchain' evolution has revolutionised data integrity and decentralised processing, impacting diverse sectors, including environmental monitoring. However, conventional blockchains face hurdles in scalability, energy efficiency, and security. This research presents QuantumForest, a consensus algorithm tailored for smart forestry, using verifiable quantum random numbers and entanglement principles. Using enhanced transaction throughput, consensus time, and energy efficiency for real-time forest data from loT devices, QuantumForest underwent simulations on a blockchain network with nodes ranging from 50 to 500. The evaluation considered factors such as network latency, data size, and environmental noise. The performance exhibited a nonlinear correlation with the number of nodes, influenced by the size of the network and the complexity of the data. Consensus time logarithmically increased with node numbers, while energy consumption demonstrated a sublinear increase. QuantumForest signifies a promising step forward in blockchain, particularly for environmental applications such as smart forestry. By integrating quantum entanglement, it fortifies security, decentralisation, and enhances transaction processing and energy efficiency. This study sets the stage for sustainable, efficient environmental monitoring through blockchain, with farreaching implications.
The development of the application of making use of Wireless Body Area Networks (WBANs) in medically created systems has presented fresh security concerns, in particular with the advent of quantum computing threatening the conventional cryptographic ideas. To proposes a new model Scalable Quantum-Intelligent Blockchain Framework (SQIBF) and a Deep Quantum Neural Architecture (DQNA) to privacy-preserving healthcare communications. The proposed framework is a synergistic approach of post-quantum lattice-based cryptography, in combination with quantum key protocols distribution schemes with federated quantum machine learning to develop multi-layered security infrastructure of the body sensor networks. We introduce Quantum Enhanced Consensus Mechanism (QECM), which deploys quantum random number generation to deliver Byzantine fault tolerance, and which can withstand symptoms of quantum-enabled parties by 97.5. The DQNA implements variational quantum gate scale used to detect textbook anomalies and categorize confidential medical data variational quantum circuit with a parameterized scale according to parameters to support the 94.3 percent mark on benchmark medical datasets with a differential privacy clarification. Experimental Assessment Simulations on simulated quantum systems and experimental WBAN testbeds have shown that it, SQIBF, can decrease the key establishing latency by approximately 40 percent when compared to classical blockchain methods using resource optimizing biosensors resource exploratory consumptions. Its model ensures the compliance of the HIPAA and GDPR requirements and homomorphic encryption layers with zero-knowledge proofs. Scalability of performance benchmarking implies up to 10,000 active sensor nodes and sub-millisecond finality of transaction. The present work introduces an end-to-end quantum resistant system to facilitate the muchneeded transitional process of quantum computing, distributed ledger technology, and health care IoT and establishes a platform of safe telemedicine infrastructure in the next generation.
The integration of blockchain technology in electronic medical records (EMRs) offers enhanced data security and integrity. However, classical blockchain systems face potential threats from quantum computing and often involve significant computation and communication costs. This paper proposes a secure framework for safeguarding EMRs using quantum blockchain technology, leveraging quantum cryptographic principles to enhance security. The proposed framework employs Quantum Key Distribution (QKD) and post-quantum cryptographic algorithms to resist quantum attacks, ensuring robust protection of sensitive data. By optimizing consensus mechanisms with quantum algorithms, with this research work, a 30% reduction in computation costs and a 25% decrease in communication overhead is achieved compared to traditional blockchain systems. These improvements are quantified through simulation results, demonstrating the framework’s efficiency and practicality. The proposed solution ensures higher security, integrity, and cost-effectiveness for managing EMRs in the face of emerging quantum threats.