Security for networked smart healthcare systems: A systematic review

Background and Objectives Smart healthcare systems use technologies such as wearable devices, Internet of Medical Things and mobile internet technologies to dynamically access health information, connect patients to health professionals and health institutions, and to actively manage and respond intelligently to the medical ecosystem's needs. However, smart healthcare systems are affected by many challenges in their implementation and maintenance. Key among these are ensuring the security and privacy of patient health information. To address this challenge, several mitigation measures have been proposed and some have been implemented. Techniques that have been used include data encryption and biometric access. In addition, blockchain is an emerging security technology that is expected to address the security issues due to its distributed and decentralized architecture which is similar to that of smart healthcare systems. This study reviewed articles that identified security requirements and risks, proposed potential solutions, and explained the effectiveness of these solutions in addressing security problems in smart healthcare systems. Methods This review adhered to the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines and was framed using the Problem, Intervention, Comparator, and Outcome (PICO) approach to investigate and analyse the concepts of interest. However, the comparator is not applicable because this review focuses on the security measures available and in this case no comparable solutions were considered since the concept of smart healthcare systems is an emerging one and there are therefore, no existing security solutions that have been used before. The search strategy involved the identification of studies from several databases including the Cumulative Index of Nursing and Allied Health Literature (CINAL), Scopus, PubMed, Web of Science, Medline, Excerpta Medical database (EMBASE), Ebscohost and the Cochrane Library for articles that focused on the security for smart healthcare systems. The selection process involved removing duplicate studies, and excluding studies after reading the titles, abstracts, and full texts. Studies whose records could not be retrieved using a predefined selection criterion for inclusion and exclusion were excluded. The remaining articles were then screened for eligibility. A data extraction form was used to capture details of the screened studies after reading the full text. Of the searched databases, only three yielded results when the search strategy was applied, i.e., Scopus, Web of science and Medline, giving a total of 1742 articles. 436 duplicate studies were removed. Of the remaining articles, 801 were excluded after reading the title, after which 342 after were excluded after reading the abstract, leaving 163, of which 4 studies could not be retrieved. 159 articles were therefore screened for eligibility after reading the full text. Of these, 14 studies were included for detailed review using the formulated research questions and the PICO framework. Each of the 14 included articles presented a description of a smart healthcare system and identified the security requirements, risks and solutions to mitigate the risks. Each article also summarized the effectiveness of the proposed security solution. Results The key security requirements reported were data confidentiality, integrity and availability of data within the system, with authorisation and authentication used to support these key security requirements. The identified security risks include loss of data confidentiality due to eavesdropping in wireless communication mediums, authentication vulnerabilities in user devices and storage servers, data fabrication and message modification attacks during transmission as well as while the data is at rest in databases and other storage devices. The proposed mitigation measures included the use of biometric accessing devices; data encryption for protecting the confidentiality and integrity of data; blockchain technology to address confidentiality, integrity, and availability of data; network slicing techniques to provide isolation of patient health data in 5G mobile systems; and multi-factor authentication when accessing IoT devices, servers, and other components of the smart healthcare systems. The effectiveness of the proposed solutions was demonstrated through their ability to provide a high level of data security in smart healthcare systems. For example, proposed encryption algorithms demonstrated better energy efficiency, and improved operational speed; reduced computational overhead, better scalability, efficiency in data processing, and better ease of deployment. Conclusion This systematic review has shown that the use of blockchain technology, biometrics (fingerprints), data encryption techniques, multifactor authentication and network slicing in the case of 5G smart healthcare systems has the potential to alleviate possible security risks in smart healthcare systems. The benefits of these solutions include a high level of security and privacy for Electronic Health Records (EHRs) systems; improved speed of data transaction without the need for a decentralized third party, enabled by the use of blockchain. However, the proposed solutions do not address data protection in cases where an intruder has already accessed the system. This may be potential avenues for further research and inquiry

Enhancing healthcare services through cloud service: a systematic review

Although cloud-based healthcare services are booming, in-depth research has not yet been conducted in this field. This study aims to address the shortcomings of previous research by analyzing all journal articles from the last five years using the preferred reporting items for systematic reviews and meta-analyses (PRISMA) systematic literature review methodology. The findings of this study highlight the benefits of cloud-based healthcare services for healthcare providers and patients, including enhanced healthcare services, data security, privacy issues, and innovative information technology (IT) service delivery models. However, this study also identifies challenges associated with using cloud services in healthcare, such as security and privacy concerns, and proposes solutions to address these issues. This study concludes by discussing future research directions and the need for a complete solution that addresses the conflicting requirements of the security, privacy, efficiency, and scalability of cloud technologies in healthcare

The Applications of the Internet of things in the Medical Field

The Internet of Things (IoT) paradigm promises to make “things” include a more generic set of entities such as smart devices, sensors, human beings, and any other IoT objects to be accessible at anytime and anywhere. IoT varies widely in its applications, and one of its most beneficial uses is in the medical field. However, the large attack surface and vulnerabilities of IoT systems needs to be secured and protected. Security is a requirement for IoT systems in the medical field where the Health Insurance Portability and Accountability Act (HIPAA) applies. This work investigates various applications of IoT in healthcare and focuses on the security aspects of the two internet of medical things (IoMT) devices: the LifeWatch Mobile Cardiac Telemetry 3 Lead (MCT3L), and the remote patient monitoring system of the telehealth provider Vivify Health, as well as their implementations

Using Blockchain Technology in Smart Life Applications

مقدمة: Blockchain هي قاعدة بيانات يتم تخزينها بترتيب زمني بطريقة آمنة ومستقرة. كانت Bitcoin هي التطبيق الأولي لتقنية Blockchain ، ولكن نظرًا لفوائدها من حيث الأمان والخصوصية والتحكم الذاتي ، فقد تم اعتمادها منذ ذلك الحين من قبل مجموعة متنوعة من التطبيقات. يتم إنشاء تقنية Blockchain عن طريق ربط الكتل معًا بشكل مشفر. نظرًا لأن كل كتلة تحتوي على كلٍ من التجزئة الخاصة بها وتجزئة الكتلة السابقة لها ، فلا يمكن لأي شخص خارجي كسر السلسلة. تُستخدم تقنية Blockchain ضمن مجموعة متنوعة من التطبيقات ، بما في ذلك الصناعية والتجارية والأمنية وسلسلة التوريد وإنترنت الأشياء وغيرها. هذا لأنه يتميز بمزايا التحكم في البيانات وتنظيمها وتخزينها. الغرض من هذه المقالة هو سرد بعض التطبيقات ومجالات التطوير الخاصة بـ Blockchain.   طرق العمل: في تقنية Blockchain ، يعد الأمان والاستقرار (الثبات) واللامركزية من بين الأشياء المهمة التي تجعل هذه التقنية مفيدة في مختلف مجالات الحياة التي تخدم المستخدم. تم استخدام هذه المزايا لحل العديد من المشكلات التي تواجه الشبكة ، بما في ذلك المشكلات المتعلقة بالإنتاجية ووقت المعالجة وقابلية التوسع. تم استخدام طرق مختلفة في الحل ، بما في ذلك العمل على تغيير هيكل الشبكة ، واختيار عقدة أساسية (المدير) ، والتعدين الموازي ، والتنافس مع عمال المناجم الآخرين. الاستنتاجات: ازداد الميل إلى استخدام تقنية Blockchain في العديد من المجالات ، بما في ذلك المالية والزراعية والتجارية والصحية وإنترنت الأشياء وغيرها ، نظرًا لمزاياها ، بما في ذلك اللامركزية والتوزيع والموثوقية والاستقرار. هناك اتجاهات أخرى عملت على تطوير أداء وكفاءة وأمان نظام Blockchain نفسه في إنترنت الأشياء والرعاية الصحية وسلسلة التوريد والقطاع المصرفي والتسويق الرقمي بالإضافة إلى الدراسات التي تشمل تحسين الكفاءة والأمان وتطوير النظام.Background: Materials and Methods:      In Blockchain technology, security, stability (immutability), and decentralization are among the important things that make this technology useful in various areas of life that serve the user. These advantages were used to solve many problems facing the network, including those of productivity, processing time, and scalability. Various methods were used in the solution, including working on a change in the network structure, choosing a basic node (the manager), parallel mining, and competing with other miners. Results:     Through recent studies, it has been shown that the Blockchain technology has been used in various fields, as it is characterized by many advantages, the most important of which are security, decentralization, and stability. Because of these advantages, it outperforms other technologies. Conclusion:     Due to its advantages, the tendency to use blockchain technology has increased in many fields, including financial, agricultural, commercial, health, the Internet of Things, and others. It includes decentralization, distribution, reliability, and stability. There are other trends that have worked to improve the performance, efficiency, and security of the blockchain system itself, In the Internet of Things, healthcare, supply chain management, the banking sector, and digital marketing In addition to studies that include improving the efficiency, security, and development of the system

Advancing Healthcare Security: A Cutting-Edge Zero-Trust Blockchain Solution for Protecting Electronic Health Records

The effective management of electronic health records (EHRs) is vital in healthcare. However, traditional systems often need help handling data inconsistently, providing limited access, and coordinating poorly across facilities. This study aims to tackle these issues using blockchain technology to improve EHR systems' data security, privacy, and interoperability. By thoroughly analyzing blockchain's applications in healthcare, we propose an innovative solution that leverages blockchain's decentralized and immutable nature, combined with advanced encryption techniques such as the Advanced Encryption Standard and Zero Knowledge Proof Protocol, to fortify EHR systems. Our research demonstrates that blockchain can effectively overcome significant EHR challenges, including fragmented data and interoperability problems, by facilitating secure and transparent data exchange, leading to enhanced coordination, care quality, and cost-efficiency across healthcare facilities. This study offers practical guidelines for implementing blockchain technology in healthcare, emphasizing a balanced approach to interoperability, privacy, and security. It represents a significant advancement over traditional EHR systems, boosting security and affording patients greater control over their health records. Doi: 10.28991/HIJ-2023-04-03-012 Full Text: PD

Using Federated Artificial Intelligence System of Intrusion Detection for IoT Healthcare System Based on Blockchain

Recently Internet of things (IoT)-based healthcare system has expanded significantly, however, they are restricted by the absence of an intrusion detection mechanism (IDS). Modern technologies like blockchain (BC), edge computing (EC), and machine learning (ML) provide a robust security solution that is well-suited to protecting patients' medical information. In this study, we offer an intelligent intrusion detection mechanism FIDANN that protects the confidentiality of medical data by completing the intrusion detection task by utilising Dwarf mongoose-optimized artificial neural networks (DMO-ANN) through a federated learning (FL) technique. In the context of recent developments in blockchain technology, such as the elimination of contaminating attacks and the provision of complete visibility and data integrity over the decentralized system with minimal additional effort. Using the model at the edges secures the cloud from attacks by limiting information from its gateway with less computing time and processing power as FL works with fewer datasets. The findings demonstrate that our suggested models perform better when dealing with the diversity of data produced by IoT devices

5G with Fog Computing based Privacy System in Data Analytics for Healthcare System by AI Techniques

Fog computing architecture is an extended version of the cloud computing architecture to reduce the load of the data transmission and storage in the cloud platform. The architecture of the fog increases the performance with improved efficiency compared with the cloud environment. The fog computing architecture uses the 5G based Artificial Intelligence (AI) technology for performance enhancement. However, due to vast range of data availability privacy is challenging in the fog environment. This paper proposed a Medical Fog Computing Load Scheduling (MFCLS) model for data privacy enhancement. The developed architecture model of optimization-based delay scheduling for task assignment in the fog architecture. The healthcare data were collected and processed with the 5G technology. The developed MFCLS model uses the entropy-based feature selection for the healthcare data. The proposed MFCLS considers the total attributes of 13 for the evaluation of features. With the provision of service level violation, the fog computing network architecture will be provided with reduced energy consumption. The developed load balancing reduced the service violation count with the provision of desired data privacy in the fog model. The estimation of the time frame is minimal for the proposed MFCLS model compared with the existing DAG model. The performance analysis expressed that SLRVM and ECRVM achieved by the proposed MFCLS are 28 and 43 respectively. The comparative examination of the proposed MFCLS model with the existing DAG model expressed that the proposed model exhibits ~6% performance enhancement in the data privacy for the healthcare data

A patient agent controlled customized blockchain based framework for internet of things

Although Blockchain implementations have emerged as revolutionary technologies for various industrial applications including cryptocurrencies, they have not been widely deployed to store data streaming from sensors to remote servers in architectures known as Internet of Things. New Blockchain for the Internet of Things models promise secure solutions for eHealth, smart cities, and other applications. These models pave the way for continuous monitoring of patient’s physiological signs with wearable sensors to augment traditional medical practice without recourse to storing data with a trusted authority. However, existing Blockchain algorithms cannot accommodate the huge volumes, security, and privacy requirements of health data. In this thesis, our first contribution is an End-to-End secure eHealth architecture that introduces an intelligent Patient Centric Agent. The Patient Centric Agent executing on dedicated hardware manages the storage and access of streams of sensors generated health data, into a customized Blockchain and other less secure repositories. As IoT devices cannot host Blockchain technology due to their limited memory, power, and computational resources, the Patient Centric Agent coordinates and communicates with a private customized Blockchain on behalf of the wearable devices. While the adoption of a Patient Centric Agent offers solutions for addressing continuous monitoring of patients’ health, dealing with storage, data privacy and network security issues, the architecture is vulnerable to Denial of Services(DoS) and single point of failure attacks. To address this issue, we advance a second contribution; a decentralised eHealth system in which the Patient Centric Agent is replicated at three levels: Sensing Layer, NEAR Processing Layer and FAR Processing Layer. The functionalities of the Patient Centric Agent are customized to manage the tasks of the three levels. Simulations confirm protection of the architecture against DoS attacks. Few patients require all their health data to be stored in Blockchain repositories but instead need to select an appropriate storage medium for each chunk of data by matching their personal needs and preferences with features of candidate storage mediums. Motivated by this context, we advance third contribution; a recommendation model for health data storage that can accommodate patient preferences and make storage decisions rapidly, in real-time, even with streamed data. The mapping between health data features and characteristics of each repository is learned using machine learning. The Blockchain’s capacity to make transactions and store records without central oversight enables its application for IoT networks outside health such as underwater IoT networks where the unattended nature of the nodes threatens their security and privacy. However, underwater IoT differs from ground IoT as acoustics signals are the communication media leading to high propagation delays, high error rates exacerbated by turbulent water currents. Our fourth contribution is a customized Blockchain leveraged framework with the model of Patient-Centric Agent renamed as Smart Agent for securely monitoring underwater IoT. Finally, the smart Agent has been investigated in developing an IoT smart home or cities monitoring framework. The key algorithms underpinning to each contribution have been implemented and analysed using simulators.Doctor of Philosoph