Digital Twins (DTs) play a crucial role in context-aware Internet of Things (IoT) applications within the healthcare sector, including the industrial healthcare domain, by facilitating the continuous sharing of sensitive and confidential patient data from physical objects in real time. This shared data is essential for treatment planning and decision-making processes, often being accessed remotely by authorized users. However, traditional security mechanisms, which rely on the integer factorization problem (IFP) and the elliptic curve discrete logarithm problem (ECDLP), are vulnerable to quantum attacks using algorithms like Shor's, posing significant risks to data protection. As a result, the healthcare sector faces several security challenges, including the vulnerability of sensitive patient data to cyberattacks, quantum threats, the risk of unauthorized access to medical devices and IoT systems, and the increasing sophistication of cybercriminals exploiting weak authentication methods. To address these issues, we propose a quantum-resistant protocol that safeguards data privacy in DT-enabled IoT healthcare applications, ensures secure transmission of information, maintains patient trust, supports long-term data confidentiality, and protects medical devices and IoT systems from potential breaches. By employing lattice-based cryptographic techniques, particularly the ring learning with errors (RLWE) problem, the proposed scheme effectively addresses contemporary security challenges, including those posed by quantum computing. Real-time experiments conducted on Raspberry Pi 4 devices, along with computational overhead analysis, demonstrate the protocol's efficiency. Additionally, formal security validation using the Scyther tool and security analysis with the RoR model reinforce the robustness of the proposed protocol. A comprehensive comparative evaluation against existing schemes highlights its lightweight, scalable, and efficient nature. Furthermore, performance evaluations in the context of unknown attacks show that the proposed scheme significantly outperforms current alternatives in terms of effectiveness.
Digital Twins (DTs) play a crucial role in context-aware Internet of Things (IoT) applications within the healthcare sector, including the industrial healthcare domain, by facilitating the continuous sharing of sensitive and confidential patient data from physical objects in real time. This shared data is essential for treatment planning and decision-making processes, often being accessed remotely by authorized users. However, traditional security mechanisms, which rely on the integer factorization problem (IFP) and the elliptic curve discrete logarithm problem (ECDLP), are vulnerable to quantum attacks using algorithms like Shor's, posing significant risks to data protection. As a result, the healthcare sector faces several security challenges, including the vulnerability of sensitive patient data to cyberattacks, quantum threats, the risk of unauthorized access to medical devices and IoT systems, and the increasing sophistication of cybercriminals exploiting weak authentication methods. To address these issues, we propose a quantum-resistant protocol that safeguards data privacy in DT-enabled IoT healthcare applications, ensures secure transmission of information, maintains patient trust, supports long-term data confidentiality, and protects medical devices and IoT systems from potential breaches. By employing lattice-based cryptographic techniques, particularly the ring learning with errors (RLWE) problem, the proposed scheme effectively addresses contemporary security challenges, including those posed by quantum computing. Real-time experiments conducted on Raspberry Pi 4 devices, along with computational overhead analysis, demonstrate the protocol's efficiency. Additionally, formal security validation using the Scyther tool and security analysis with the RoR model reinforce the robustness of the proposed protocol. A comprehensive comparative evaluation against existing schemes highlights its lightweight, scalable, and efficient nature. Furthermore, performance evaluations in the context of unknown attacks show that the proposed scheme significantly outperforms current alternatives in terms of effectiveness.
The rapid adoption of Internet of Medical Things (IoMT) devices enables real-time patient monitoring and remote diagnostics and has revolutionized healthcare delivery. Traditional cryptographic schemes like RSA and ECC, which rely on meaningful mathematical challenges, are under great threat from quantum computing, threatening sensitive medical data confidentiality and integrity. This paper proposes a quantum-resistant healthcare security framework based on lattice-based cryptographic primitives such as Learning With Errors (LWE), Ring-LWE (RLWE), and Short Integer Solution (SIS). To this end, we design a five-phase IoMT-friendly framework—Initialization, Registration, Authentication, Data Exchange, and Treatment—where each phase is backed up by lightweight cryptography primitives that can be easily implemented on the low-resource IoMT devices. Relative to the state-of-the-art lattice- and hash-based constructions, our framework involves 50-75% smaller ciphertext sizes, up to a 50% reduction of the communication overhead, and nearly 60% less in computational cost. Furthermore, the solution relies on zero-knowledge proofs, homomorphic encryption as well and attribute-based access control to guarantee strong security and privacy. Using the AVISPA tool, the framework is formally verified, showing its resistance against classical and quantum adversaries. Focusing on tangible healthcare threats, including data tampering and unlicensed access to patient diagnostics, this research paves the way for scalable, efficient, and quantum-resistant medical data protection. Our results pave the way for future investigations into secure post-quantum healthcare and IoT applications.
The rapid growth of the Internet of Things (IoT) has connected billions of smart devices across healthcare, transportation, industrial automation, and smart home environments. While IoT has enhanced automation and data-driven decision-making, its widespread deployment has also increased the risk of cyberattacks. Conventional public-key cryptographic algorithms such as RSA and Elliptic Curve Cryptography (ECC) are vulnerable to future quantum computing attacks, particularly those based on Shor's algorithm. This paper proposes a Quantum-Resistant Cryptographic Framework (QRCF) for secure IoT communication using lattice-based cryptography integrated with lightweight authentication and efficient key management. The framework is designed to meet the computational limitations of IoT devices while ensuring long-term confidentiality and integrity. Performance evaluation demonstrates improvements in security resilience, authentication efficiency, and communication reliability compared with traditional cryptographic approaches. The proposed framework offers a scalable and future-ready solution for protecting IoT ecosystems in the post-quantum era.
Internet of Medical Things (IoMT) system is a collection of devices and software which are applied in medical care domains. In a IoMT system, patients and doctors conduct remote diagnosis and treatment through a health data sharing scheme. These data sharing schemes faces privacy challenges if the medical information gets leaked. However, the existing privacy-preserving data sharing schemes usually use classical encryption/signature algorithm, which will turn to be not secure under the development of quantum computer. In this paper, we propose a privacy-preserving data sharing scheme using lattice-based cryptography, the ring learning with errors (RLWE) cryptography. Our scheme integrates both quantum-resistant encryption and digital signature algorithm based on RLWE, in order to realize the resistance to quantum attack for the whole life cycle of data. In addition, the performance evaluation shows that the proposed scheme gets 75.7% higher efficiency than the existing schemes.
Abstract Task offloading frameworks play a crucial role in modern healthcare by optimizing resource utilization, reducing computational burdens, and enabling real-time medical decision-making. However, existing Digital Twin (DT)-based healthcare models suffer from high latency, inefficient resource allocation, cybersecurity vulnerabilities, and computational limitations when processing large-scale patient data. These constraints pose significant risks in time-sensitive applications such as ICU monitoring, robotic-assisted surgeries, and telemedicine. To address these limitations, this paper introduces a Quantum-Enhanced DT-IoT framework, integrating Artificial Intelligence (AI), Quantum Computing (QC), DT, and the Internet of Things (IoT) for real-time, secure, and efficient healthcare task offloading. The proposed system introduces two key optimization algorithms: (1) DTH-ATB-MAPPO, which dynamically adjusts task scheduling and resource distribution, and (2) AQDT-IoT, which enhances computational efficiency and cybersecurity compliance in 6 G-enabled IoT networks. By leveraging Approximate Amplitude Encoding (AAE) and Grover’s search, the framework enhances task offloading efficiency, enabling faster decision-making and optimized resource distribution across 6 G-enabled IoT networks. Empirical evaluations show that quantum preprocessing improved Task Offloading Success Rate (TOSR) by 32% and reduced the Error Rate (ER) by 80%, significantly outperforming traditional DT-based healthcare models. These enhancements enable. Additionally, theoretical analysis demonstrates computational speed enhancements, adaptive cybersecurity mechanisms, and improved system scalability, positioning this framework as a viable candidate for future cloud-based quantum healthcare infrastructures, even in resource-constrained hospital environments.
Abstract In internet of things (IOT) healthcare systems, sensitive patient information is transmitted over the network to medical professionals. Numerous lightweight authentication protocols have been proposed; however, most of them remain vulnerable to various cyberattacks, allowing attackers to eavesdrop on or manipulate transmitted data. We examine several recently proposed lightweight authentication schemes for healthcare systems. Our security analysis demonstrates that these schemes remain vulnerable to malicious gateway attacks, desynchronization attacks, and key screw attacks. .To address these issues and ensure post- quantum security in healthcare IoT, we propose a post-quantum key establishment protocol based on lattice- based cryptography (LWE). the proposed scheme prevents the gateway from accessing both the secret keys and their parameters, thereby eliminating the possibility of malicious gateway attacks. The proposed protocol ensures user anonymity, forward secrecy, and resistance to impersonation, key screw, and desynchronization attacks.. The proposed protocol ensures secure and efficient establishment of three-round key establishment among entities . Our performance evaluation shows that the proposed scheme achieves lower computation and communication overhead compared to recent related works. The security of the protocol is thoroughly analyzed through informal reasoning, Burrows–Abadi–Needham (BAN) logic, and ProVerif, confirming its robustness and suitability for resource-constrained IoT-based healthcare environments.
The integration of consumer-centric digital twin (CCDT) technology is set to transform healthcare systems, enabling blockchain-based solutions for enhanced medical services. By precisely simulating patients and medical processes, CCDT establish a link to the virtual healthcare environment, supporting improved diagnosis, real-time monitoring, and predictive analytics. Blockchain technology is critical in connecting the physical and virtual health care worlds, providing secure storage, efficient communication, reduced computational costs, and reliable hosting services. However, the security of patient data and its digital twin counterpart stored on the blockchain remains a potential vulnerability, as any alteration or unauthorized access to this information could pose significant risks. To address this challenge, we propose a blockchain-enabled quantum encryption protocol for CCDT healthcare networks to ensure secure communication. The proposed protocol leverages blockchain to authenticate patients without relying on third-party entities. At the same time, a secure quantum encryption mechanism ensures that CCDT do not need to authenticate repeatedly when interacting with multiple healthcare providers. A performance evaluation demonstrates the effectiveness of the proposed scheme compared to existing encryption methods. The results indicate that the suggested protocol is resilient against various security threats, showcasing its significant potential for enhancing communication security within CCDT healthcare networks.