Hospitals are increasingly under pressure because of the growing volume of imaging tests carried out, but also because of the sophistication of the attacks by the cybercriminal. Conventional security systems are unable to meet today's challenges to patient records and radiological data. In this research, these challenges are addressed directly by designing an advanced defence system that is specifically designed for medical imaging archiving and communication systems in radiology departments. Architected an extensive protective architecture with seven layers that are interconnected. It's a combination of cutting-edge encryption techniques capable of resisting the powerful future quantum computer, authentication processes that validate every access attempt on the fly, data patterns that are learned, suspicious activity recognized, blockchain technology that makes data impossible to tamper with, and predictive algorithms that foresee threats before they happen. Our system is proactive, identifying and neutralising threats at an early stage, instead of reacting to attacks as they happen. Real-world validation took place within five different hospital networks, covering two years, and thus subjected the framework to the real conditions of operation and to real cyber threats. The results of the system's performance were outstanding – the system had a rate of 99.9% accuracy in detecting malicious activities and a rate of 0.15% False Alarms. The overhead for security operations was just 23 milliseconds, not affecting clinical workflow. Most impressively, there was a 67% reduction in the number of attempts to break in onto the network unauthorisedly, due to the formidable defence measures that they faced.Our framework thwarted 847 real tests against it, ranging from sophisticated persistent intrusions and previously unknown software vulnerabilities to attempts by ransomware to encrypt patient information – all during testing. The system ensured complete compliance with healthcare privacy laws from various jurisdictions, aligning with the American HIPAA regulations, the European GDPR and the new quantum-security protocols. In essence, this is a paradigm shift in medical imaging security, offering healthcare institutions proactive and intelligent protection that safeguards patient privacy and institutional integrity in the face of future threats.
Wang Lei, Jasni Mohamad Zain, Nur Atiqah Sia Abdullah, Marina Yusoff · 7 authors
The proliferation of Internet of Medical Things devices within the predictive healthcare paradigm necessitates robust, privacy-centric collaborative learning frameworks to detect and mitigate rapid clinical deterioration. Traditional federated learning methodologies, while attempting to preserve patient data locality, are fundamentally constrained by multi-round gradient synchronization protocols, imposing prohibitive communication latency and remaining susceptible to false negatives under extreme non-independent and identically distributed conditions. To address these challenges, this study introduces the Feature-Augmented Analytic Federated (FaFL) Architecture, which fundamentally replaces iterative gradient synchronization with a single-round closed-form computational paradigm. By instituting a proactive feature mixing mechanism via a decoupled zero-knowledge proof global buffer, the proposed framework empowers local grassroots nodes to neutralize extreme clinical heterogeneity in a single phase. The architecture employs a closed-form analytic solution combined with a trace-weighted absolute aggregation protocol to rigorously guarantee stochastic convergence and absolute cryptographic resilience without requiring recursive parameter exchanges. Extensive empirical evaluations against existing baselines under severe Dirichlet non-independent and identically distributed conditions and Byzantine poisoning attacks demonstrate that the framework fundamentally eradicates high false-negative rates in resource-constrained clinics. Consequently, the proposed architecture robustly guarantees generalization stability, substantially outperforms existing paradigms in predictive fidelity and computational efficiency, and establishes a new operational standard for mission-critical clinical networks.
Internet of Things (IoT) technologies in the healthcare industry, also known as the Internet of Medical Things (IoMT), have proven to greatly improve patient monitoring, diagnostics, and clinical decision-making. The increasing prevalence of resource-challenged medical devices, wireless connectivity, and cloud services, however, has brought new risks around security and privacy concerns that can now directly impact patient safety and data integrity. In this paper, a thorough study of 41 peer-reviewed research papers from January 2018 through May 2025 revealed the current state of security vulnerabilities and resilience strategies in healthcare IoT systems. It provides a comprehensive analysis of security threats at the device, network, and application levels such as unauthorized access, malware and ransomware, data breaches, and denial-of-service attacks delivered in a systematic manner. This contrasts with existing surveys, which consider single security mechanisms and improve upon various multi-layered security means such as AI-enabled anomaly detection, blockchain-based authentication and auditability, low-compute cryptographic techniques, and privacy-preserving methods such as federated learning. The outcomes also show that although emerging technologies add a great deal of security and trust capabilities, issues on scalability, interoperability, deployment, and regulations are not yet fully addressed. This review highlights important knowledge gaps and offers structured knowledge and future directions for research to address the design of secure, resilient, and practically deployable IoMT architectures for real-world healthcare environments.
Abstract Rural health systems are networks, which are geographically disseminated and resource limited, in which inefficient inter-hospital coordination has a strong influence on patient outcomes, operational stability and surgical resilience. Regardless of the development of smart hospital technologies, such as 5G-enabled communication opportunities, the integration of digital coordination centers, and telemedicine, the current frameworks are more focused on streamlining intra-hospital processes instead of the inter-hospital distribution of resources. This structural disintegration leads to slow shifts, poor use of bed space, inaccessibility of specialists, and poor responsiveness to surges. This paper suggests Smart Inter-Hospital Representation Network (SIHCN) to be a rural hospital ecosystem distributed systems architecture. The framework combines a granted blockchain based resource registry, real-time capacity monitoring strategies, specialist allocation registries, and adaptive routing logic into a coordination infrastructure. The proposed architecture will be able to guarantee decentralized system control against centralized command models, fault tolerance, and scalable interoperability among autonomous hospital nodes. The paper introduces a conceptual systems model that specifies the network topology, operational data flow, distributed resource synchronization and performance evaluation metrics. The simulation modeling is based on a scenario simulation that assesses the system performance when under routine and emergency surge conditions, showing that the transfer latency, resource balancing, and coordination efficiency is improved. The results make distributed ledger-based coordination a potential engineering technique in enhancing the resilience of rural health networks. This study also addresses the Healthcare Systems Engineering field by re-conceptualizing rural hospital coordination as a distributed resource optimization problem and suggesting an architecture-layer solution that can be applied to low-density, high-variability healthcare settings.
R. Yuvarani, R Mahaveerakannan, T. Tamilvizhi, L Kartheesan
The integration of blockchain into 6G-enabled Internet of Medical Things (IoMT) networks promises secure and decentralized communication but introduces challenges related to energy efficiency, latency, and authentication overhead. Existing clustering and security schemes fail to balance these aspects effectively in heterogeneous networks. This paper proposes a novel energy-aware cluster head (CH) selection framework using Artificial Democratic Cuckoo Glowworm Remora Optimization (ADCGRO), integrated with a lightweight blockchain layer for secure authentication and data integrity. The system optimizes task allocation across advanced, intermediate, and normal IoMT devices to minimize energy depletion while meeting ultra-reliable low-latency communication (URLLC) requirements. Simulation results demonstrate that the proposed approach enhances network lifetime by 27%, reduces average latency by 35%, and achieves 99% authentication accuracy, surpassing baseline protocols such as LEACH and HEED. These results highlight the effectiveness of combining ADCGRO-based optimization with blockchain to enhance performance and security in 6G wireless networks.
Munir Hussain, Amjad Mehmood, Muhammad Altaf Khan, Jaime Lloret · 5 authors
The recent developments in telecommunication technologies and monitoring devices have brought many changes in modern electronic healthcare systems (EHSs) by improving quality and decreasing healthcare expenses. Despite the benefits, they have privacy and security issues because the communication between patients and service providers takes place generally over public channels. Several user authentication protocols using distributed ledger technology (DLT) have recently been proposed to address these issues in EHSs. However, many are still vulnerable to a single point of failure (SPoF), privacy, and security attacks. Besides, they suffered from high communication and computational costs. Therefore, in this paper, we proposed a user authentication protocol using DLT to avoid these issues. A Burrows-Abadi-Needham (BAN) logic proof method has been used to check the security of the proposed protocol and ensure it achieves the desired security goals. In addition, an informal security analysis has been conducted to verify its important security requirements. A formal security analysis has been performed via the Automated Validation of Internet Security Protocols and Applications (AVISPA) tool and Real-or-Random (ROR) model for further security strength. The results demonstrate that the proposed user authentication protocol is SAFE against all types of Man-in-the-Middle (MitM) attacks, impersonation, replay, and forgery attacks . Finally, performance analysis has been performed and results show that it achieves better performance by consuming 29.63 % and 13.21 % less communication and computational overheads as compared to existing related user authentication protocols. The security and performance analysis make it a more appropriate choice for the EHSs.
The evolution toward sixth-generation (6G) wireless communication networks introduces unparalleled opportunities, alongside complex security and privacy challenges. This paper presents a broad and flexible roadmap for securing 6G networks, exploring the diverse range of threats posed by advanced technologies such as Distributed Ledger Technology (DLT), quantum computing, and AI/ML. Rather than focusing on a singular problem or solution, the paper emphasizes the need for adaptable frameworks capable of addressing the multifaceted and evolving security landscape of 6G. Key areas of focus include quantum-safe cryptography, AI-based threat detection, and privacy-preserving technologies like homomorphic encryption and federated learning. The paper also underscores the critical role of standardization efforts by key organizations such as ETSI, ITU, and 3GPP in shaping secure, resilient, and trustworthy 6G networks. By maintaining a general perspective, this roadmap offers a foundation for future research and collaboration, guiding the development of context-specific security solutions as 6G technology advances.
Inas Al Khatib, Abdulrahim Shamayleh, Malick Ndiaye
In recent years, the Internet of medical things (IoMT) has become a significant technological advancement in the healthcare sector. This systematic review aims to identify and summarize the various applications, key challenges, and proposed technical solutions within this domain, based on a comprehensive analysis of the existing literature. This review highlights diverse applications of the IoMT, including mobile health (mHealth) applications, remote biomarker detection, hybrid RFID-IoT solutions for scrub distribution in operating rooms, IoT-based disease prediction using machine learning, and the efficient sharing of personal health records through searchable symmetric encryption, blockchain, and IPFS. Other notable applications include remote healthcare management systems, non-invasive real-time blood glucose measurement devices, distributed ledger technology (DLT) platforms, ultra-wideband (UWB) radar systems, IoT-based pulse oximeters, accident and emergency informatics (A&EI), and integrated wearable smart patches. The key challenges identified include privacy protection, sustainable power sources, sensor intelligence, human adaptation to sensors, data speed, device reliability, and storage efficiency. The proposed mitigations encompass network control, cryptography, edge-fog computing, and blockchain, alongside rigorous risk planning. The review also identifies trends and advancements in the IoMT architecture, remote monitoring innovations, the integration of machine learning and AI, and enhanced security measures. This review makes several novel contributions compared to the existing literature, including (1) a comprehensive categorization of IoMT applications, extending beyond the traditional use cases to include emerging technologies such as UWB radar systems and DLT platforms; (2) an in-depth analysis of the integration of machine learning and AI in IoMT, highlighting innovative approaches in disease prediction and remote monitoring; (3) a detailed examination of privacy and security measures, proposing advanced cryptographic solutions and blockchain implementations to enhance data protection; and (4) the identification of future research directions, providing a roadmap for addressing current limitations and advancing the scientific understanding of IoMT in healthcare. By addressing current limitations and suggesting future research directions, this work aims to advance scientific understanding of the IoMT in healthcare.
Dorothy Gatwiri Bundi, Stephen Mutua, Simon Karume
This study of the literature delves into the complex area of medical systems interoperability, focusing on mitigating variables that impact security and data transfer at the structural and semantic levels. In the era of digital healthcare, the secure sharing of medical data is crucial, and this study looks at how Distributed Ledger Technologies (DLTs) can play a major role in addressing these challenges. Complex interoperability issues that come from differences in communication protocols, data formats, established data structures, data models, and data meaning and codification methodologies face the healthcare industry. These problems typically impede the seamless transmission of electronic medical records between healthcare systems. Because of their decentralized structure and cryptographic foundation, DLTs offer a workable solution to these issues. By critically evaluating previous research and case studies, DLTs may be able to lessen these interoperability issues, as this literature review illustrates. Since DLTs provide an immutable and secure platform for the transmission of medical data, guaranteeing data integrity and confidentiality, they are a natural fit for the sensitive nature of healthcare data. Their importance in creating safe communication protocols, enhancing the meaning of data, and defining models and formats for data is emphasized in this review. A comprehensive architecture for DLT interoperability in healthcare is also recommended by the research. This framework encourages the development of DLT integration, shared data models, standardized data formats, and governance and policy. By implementing this strategy and strengthening secure medical data sharing, healthcare organizations and governments may increase the efficiency, precision, and speed of healthcare delivery. The crucial role that DLTs play in removing the structural and semantic barriers to safe medical systems interoperability is highlighted in the conclusion of this literature review. By adopting DLTs, the healthcare sector may usher in a new era of standardized, safe, and efficient medical data transmission, which will ultimately benefit both patients and healthcare providers. This study shows how distributed ledger technologies (DLTs) have the potential to revolutionize the healthcare industry by enabling the secure and meaningful exchange of medical data between different systems, thereby improving patient care and healthcare outcomes.
Wireless body area networks (WBAN) are essential components of intelligent healthcare monitoring techniques. Especially, when the number and datatype inWBANincreases. InWBAN, secure multidimensional data aggregation received a lot of attention. However, the related schemes consume more computational and communication overhead to encrypt/decrypt the multidimensional health reports. In this paper, a blockchain-assisted scalable and secure multidimensional data aggregation scheme is introduced for fog-basedWBAN. The multidimensional health data are efficiently generated, encrypted, and decrypted by using the Paillier cryptosystem. Further, the batch verification method is used to achieve efficient authentication. The proposed system offers significant security attributes with less computation and communication overhead in comparison with competing systems. Further, it supports statistical analyses such as summation and variance to analyze the received health report.
Implantable medical devices (IMDs) in medical sciences have provided a quantum leap in network transformation. The communication network with IMDs typically has a wireless radio frequency (RF) telemetry or wired connection. IMDs, being devices, have more computing, communication capabilities and decision-making. Furthermore, these devices are being used to improve patients’ quality of life by medicating various chronic diseases. The captured data is stored in a medical server through a controller node. Our work focuses on wireless communication, so sensitive patient data over a public channel might be tampered with or eavesdropped by unauthorised access. Furthermore, the leakage of health data and malfunctioning of IMDs are vital in constructing cryptographic protocols, particularly in the design of remote user authentication. In this paper, we proposed a novel secure remote user authentication scheme using a lightweight consortium blockchain for the communication network with IMDs.
The hybrid wireless sensor network is made up of Wireless Body Area Network (WBAN). Generally, many hospitals use cellular networks to support telemedicine. To provide the treatment to the patient on time, for this, an early diagnosis is required, for treatment. With the help of WBANs, collections and transmissions of essential biomedical data to monitor human health becomes easy. Compressor Sensing (CS) is an emerging signal compression/acquisition methodology that offers a protruding alternative to traditional signal acquisition. The proposed mechanism reduces message exchange overhead and enhances trust value estimation via response time and computational resources. It reduces cost and makes the system affordable to the patient. According to the results, the proposed scheme in terms of Compression Ratio (CR) is 18.18% to 88.11% better as compared to existing schemes. Also in terms of Percentage Root-Mean-Squared Difference (PRD) value, the proposed scheme is 18.18% to 34.21% better than with respect to existing schemes. The consensus for any new block is achieved in 24% less time than the Proof-of-Work (PoW) approach. The shallow CPU usage is required for the leader election mechanism. CPU utilization while the experiment lies in the range of 0.9% and 14%. While simulating a one-hour duration, the peak CPU utilization is 21%.
Arun Sekar Rajasekaran, Azees Maria, R. Maheswar, Josip Lörincz
The Internet of Health Things (IoHT) has emerged as an attractive networking paradigm in wireless communications, integrated devices and embedded system technologies. In the IoHT, real-time health data are collected through smart healthcare sensors and, in recent years, the IoHT has started to have an important role in the Internet of Things technology. Although the IoHT provides comfort in health monitoring, it also imposes security challenges in maintaining patient data confidentiality and privacy. To overcome such security issues, in this paper, a novel blockchain-based privacy-preserving authentication scheme is proposed as an approach for achieving efficient authentication of the patient without the involvement of a trusted entity. Moreover, a secure handover authentication mechanism that ensures avoiding the patient re-authentication in multi-doctor communication scenarios and revoking the possible malicious misbehavior of medical professionals in the IoHT communication with the patient is developed. The performance of the proposed authentication and handover scheme is analyzed concerning the existing state-of-the-art authentication schemes. The results of the performance analyses reveal that the proposed authentication scheme is resistant to different types of security attacks. Moreover, the results of analyses show that the proposed authentication scheme outperforms similar state-of-the-art authentication schemes in terms of having lower computational, communication and storage costs. Therefore, the novel authentication and handover scheme has proven practical applicability and represents a valuable contribution to improving the security of communication in IoHT networks.
In this paper, we introduce SwarMED, a decentralized yet high throughput interoperability system for big biomedical data. SwarMED uses Etehreum blockchain for trustless security and Swarm p2p storage to handle high throughput transaction of big data. In SwarMED, we developed an indexing mechanism over the immutable storage of Swarm to achieve high-throughput while sharing millions of patient records and images among multiple parties. SwarMED achieved a high throughput of 250K medical records per second over a private network constructed over LSU-HPC cluster. This high throughput is 9x more comparing to conventional way of using p2p storage in conjunction with blockchain. This high throughput enables the patients to get realtime access to his comprehensive medical history and scientists to gain real-time access to different medical data for collaborative research complying to the constraints posed by existing laws. Our system-level analysis over different design alternatives over different transfer and storage architectures shows that, p2p storage platforms automatically provide significantly better scalability over traditional HTTP with increasing number of clients. Swarm provides 2x more I/O throughput and 10x less latency than IPFS, another p2p storage system making it a better choice for decentralized big data transaction.
Paola Torrico Morón, Salma Salimi, Jorge Peña Queralta, Tomi Westerlund
Systems for relative localization in multi-robot systems based on ultra-wideband (UWB) ranging have recently emerged as robust solutions for GNSS-denied environments. Scalability remains one of the key challenges, particularly in ad-hoc deployments. Recent solutions include dynamic allocation of active and passive localization modes for different robots or nodes in the system. With larger-scale systems becoming more distributed, key research questions arise in the areas of security and trustability of such localization systems. This paper studies the potential integration of collaborative-decision making processes with distributed ledger technologies. Specifically, we investigate the design and implementation of a methodology for running an UWB role allocation algorithm within smart contracts in a blockchain. In previous works, we have separately studied the integration of ROS2 with the Hyperledger Fabric blockchain, and introduced a new algorithm for scalable UWB-based localization. In this paper, we extend these works by (i) running experiments with larger number of mobile robots switching between different spatial configurations and (ii) integrating the dynamic UWB role allocation algorithm into Fabric smart contracts for distributed decision-making in a system of multiple mobile robots. This enables us to deliver the same functionality within a secure and trustable process, with enhanced identity and data access management. Our results show the effectiveness of the UWB role allocation for continuously varying spatial formations of six autonomous mobile robots, while demonstrating a low impact on latency and computational resources of adding the blockchain layer that does not affect the localization process.
), security and energy efficiency achievements are the major issues in the WBAN-IoT environment. Existing schemes for these three issues fail to achieve them since nodes are resource constrained and hence delay and the energy consumption is minimized. In this paper, a blockchain-assisted delay and energy aware healthcare monitoring (B-DEAH) system is presented in the WBAN-IoT environment. Both body sensors and environment sensors are deployed with dual sinks for emergency and periodical packet transmission. Various processes are involved in this paper, and each process is described as follows: Key registration for patients using an extended version of the PRESENT algorithm is proposed. Cluster formation and cluster head selection are implemented using spotted hyena optimizer. Then, cluster-based routing is established using the MOORA algorithm. For data transmission, the patient block agent (PBA) is deployed and authenticated using the four Q curve asymmetric algorithm. In PBA, three entities are used: classifier and queue manager, channel selector and security manager. Each entity is run by a special function, as packets are classified using two stream deep reinforcement learning (TS-DRL) into three classes: emergency, non-emergency and faulty data. Individual packets are put into a separate queue, which is called emergency, periodical and faulty. Each queue is handled using Reyni entropy. Periodical packets are forwarded by a separate channel without any interference using a multi objective based channel selection algorithm. Then, all packets are encrypted and forwarded to the sink nodes. Simulation is conducted using the OMNeT++ network simulator, in which diverse parameters are evaluated and compared with several existing works in terms of network throughput for periodic (41.75 Kbps) and emergency packets (42.5 Kbps); end-to-end delay for periodic (0.036 s) and emergency packets (0.028 s); packet loss rate (1.1%); residual energy in terms of simulation rounds based on periodic (0.039 J) and emergency packets (0.044 J) and in terms of simulation time based on periodic (8.35 J) and emergency packets (8.53 J); success rate for periodic (87.83%) and emergency packets (87.5%); authentication time (3.25 s); and reliability (87.83%).
Md. Shahjalal, Md. Mainul Islam, Md Morshed Alam, Yeong Min Jang
Low-power, low-cost, and long-range connectivity for the Industrial Internet of Things (IIoT) networks are the key stipulations, nowadays. However, implementing a cost-effective, flexible, and feasible system considering server and networking security is still an open challenge. In this article, a complete end-to-end long-range wide area network (LoRaWAN) system has been demonstrated by implementing blockchain-based secure distributed data management, which is applicable in various secure IIoT applications. Dynamic data collected by multiple LoRa sensors are encrypted in a LoRa server, and the encrypted content is automatically stored in the InterPlanetary file system (IPFS) to ensure data confidentiality, integrity, and availability. To achieve data consistency, the content IDs collected from the IPFS are stored in the quorum blockchain with consortium setup using a smart contract. The consortium network is maintained by the Raft consensus algorithm employing seven nodes. The design architecture of the hardware used for both LoRa transmitting node and gateway has been described in comprehensive manners. The performance of the LoRaWAN system is analyzed by the received signal strength indicator, the communications range, and packet loss rate metrics in both line-of-sight and nonline-of-sight test systems. The data management scheme is implemented in Python, and the performance is evaluated in terms of transaction time and block size.
This document presents the final design of the 5GZORRO high-level architecture, which targets the achievement and implementation of the innovative 5G networks and services vision described above. More specifically, this deliverable is intended as a self-contained document, which merges the original content of deliverables D2.2 and D2.3 (that present the initial and the updated 5GZORRO high-level architecture respectively) and further improves them to align the 5GZORRO architecture functionalities with the feedback from the platform implementation undergoing in WP3 and WP4. With this document, the goal is to have a single source of information for the 5GZORRO high-level architecture, which includes the whole set of services offered, functionalities supported, and operational workflows implemented.<br> In practice, in alignment with the original approach proposed and described in D2.2 and D2.3, the architecture follows a principle of service-based architecture, similar to the 5G Service-based architecture defined in 3GPP and in the ETSI Zero touch network and Service Management. Integrating SDN/NFV and Cloud native orchestration technologies with a Permissioned Distributed Ledger infrastructure, the 5GZORRO architecture offers services for:<br> • cross-domain network slicing,<br> • resource and service offering via marketplaces,<br> • discovery, intelligent selection and trading of resources and Services via Smart Contracts<br> • zero-touch network slice and service lifecycle management<br> • cross-stakeholder e-license management<br> • SLA monitoring & breach prediction<br> • security and trust across multiple domains.<br> The realization of these services is made possible through the interaction of various functions for slice orchestration, network intelligence and analytics, security and trust, management of virtualized resources, all executed for multi-domain and single domain scopes. Moreover, 5GZORRO leverages many state-of-the-art technologies and standards for virtualization, NFV, Cloud Native platforms and services, zero touch, SDN, distributed ledgers, data lakes, which have been extensively reviewed to summarise the specific positioning of the 5GZORRO innovative proposition.
Over the past several years, the adoption of HealthCare Monitoring Systems (HCS) in health centers and organizations like hospitals or eldery homes growth significantly. The adoption of such systems is revolutionized by a propelling advancements in IoT and Blockchain technologies. Owing to technological advancement in IoT sensors market, innovations in HCS to monitor patients health status have motivated many countries to strength their efforts to support their citizens with such care delivery systems under the directives of a physician who has access to patient's data. Nevertheless, secure data sharing is a principal patient's concern to be comfort to use such systems. Current HCS are not able to provide reassuring security policies. For that, one of our focus in this work, is to provide security countermeasures, likewise cost-efficient solution for HCS by integrating storage model based on Blockchain and Interplanetary File Systems (IPFS). Blockchain technology is an emerging solution in pharmaceutical industry and starts to take place for HCS and allows HealthCare providers to track connected devices and control access to shared data, hence protecting patients' privacy. Furthermore, the addition of Edge and Fog computing has improved HCS to react in real-time and enhance their reliability. A variety of communication protocols can connect sensor devices to edge/Fog layer and the best choice will depend upon connectivity requirements: range, bandwidth, power, interoperability, security, and reliability. Instead, systems efficiency would decline and hurt if communication protocol is inconsistent. LoRa (Long Range) communications technology is emerging as the leader among Low-Power Wide-Area Networks (LPWANs) entering the IoT domain benefiting from many features such as long-range distances and low power consumption. This work proposes LoRaChainCare, an architecture model for HCS which combines the technologies Blockchain, Fog/Edge computing, and the LoRa communication protocol. A real implementation of LoRaChainCare system is presented and evaluated in terms of cost, run time and power consumption.
Nowadays, continuous monitoring of a patient’s healthcare data has become a critical factor in human well-being. However, with the rapid advancement of wireless technology, doctors and healthcare professionals can monitor the patient’s healthcare data in real time. But to access the confidential patient’s data which is transferred through the open wireless medium, the secure transmission plays an important role. In this work, the privacy and the anonymity of the end-users (patient/doctor) are preserved using an anonymous blockchain-based authentication scheme. Moreover, in this work initially, mutual authentication is performed between the end-users, followed by encryption and decryption of confidential data. In addition, to avoid reauthentication of the patient again during the movement of a patient from one doctor to another, a transfer authentication protocol is performed between the doctors which enhances performance analysis. The security analysis section illustrates the withstanding capability of the proposed work against various vulnerable attacks. Finally, performance investigation of the proposed work reveals a reduction in computational and communication costs when compared to existing related works.
Victor Pasknel de Alencar Ribeiro, Raimir Holanda Filho, Alex Ramos, Joel J. P. C. Rodrigues
Low-Power Wide-Area Network (LPWAN) is a new type of wireless technology that offers long range communication for devices in the Internet of Things (IoT) and LoRaWAN is one of the main technologies currently available to enable LPWAN environments. In the LoRaWAN architecture, the Join Server is a key component and is responsible for security tasks, such as authentication and key management. However, the Join Server acts as a Single Point of Failure (SPOF) since all encryption keys are stored centrally. Then, this paper presents a secure and fault-tolerant architecture to increase the levels of security and availability in LoRaWAN. A permissioned blockchain and smart contracts are used to replace the Join Server and solve the SPOF problem. A working prototype was created using open-source tools in order to evaluate the feasibility of the proposed architecture. Additionally, the performance of a blockchain network was analyzed in a cloud environment under multiple workloads and fault-tolerance experiments were performed to evaluate the impact of network failures. The results show a trade-off between availability and performance when choosing the number of blockchain peers in small scenarios. However, this behavior is reversed in large scenarios where the performance of multiple peers is best suited.
With the rapid advancement of the Internet of Things (IoT), the typical application of wireless body area networks (WBANs) based smart healthcare has drawn wide attention from all sectors of society. To alleviate the pressing challenges, such as resource limitations, low-latency service provision, mass data processing, rigid security demands, and the lack of a central entity, the advanced solutions of fog computing, software-defined networking (SDN) and blockchain are leveraged in this work. On the basis of these solutions, a task offloading strategy with a centralized low-latency, secure and reliable decision-making algorithm having powerful emergency handling capacity (LSRDM-EH) is designed to facilitate the resource-constrained edge devices for task offloading. Additionally, to well ensure the security of the entire network, a comprehensive blockchain-based two-layer and multidimensional security strategy is proposed. Furthermore, to tackle the inherent time-inefficiency problem of blockchain, we propose a blockchain sharding scheme to reduce system time latency. Extensive simulation has been conducted to validate the performance of the proposed measures, and numerical results verify the superiority of our methods with lower time-latency, higher reliability and security.