An integrated framework for privacy protection in IoT — Applied to smart healthcare

Alraja, Mansour Naser; Barhamgi, Hanadi; Rattrout, Amjad; Barhamgi, Mahmoud

doi:10.1016/j.compeleceng.2021.107060

Cited by 14 publications

(13 citation statements)

References 17 publications

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“…To evaluate the effectiveness of the categorization techniques that were put into practice, the samples needed for this study were taken from a selection of samples [ 24 ]. Also, in furthermore to the vital features that have been applied in recent research to predict CKD, several additional clinical symptoms are taken into consideration based on the proposed model [ 25 ]. These symptoms significantly contribute to the accuracy with which CKD and its severity degree can be predicted [ 26 ].…”

Section: Related Workmentioning

confidence: 99%

Smart Health Monitoring System with Wireless Networks to Detect Kidney Diseases

Rathee¹,

Vinmathi²,

Priya³

et al. 2022

Computational Intelligence and Neuroscience

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It is essential to change health services from a hospital to a patient-centric platform since medical costs are steadily growing and new illnesses are emerging on a worldwide scale. This study provides an optimal decision support system based on the cloud and Internet of Things (IoT) for identifying Chronic Kidney Disease (CKD) to provide patients with efficient remote healthcare services. To identify the presence of medical data for CKD, the proposed technique uses an algorithm named Improved Simulated Annealing-Root Mean Square -Logistic Regression (ISA-RMS-LR). The four subprocesses that make up the proposed model are a collection of data, preprocessing, feature selection, and classification. The incorporation of Simulated Annealing (SA) during Feature Selection (FS) enhances the ISA-RMS-LR model’s classifier outputs. Using the CKD benchmark dataset, the ISA-RMS-LR model’s efficacy has been verified. According to the experimental findings, the proposed ISA-RMS-LR model effectively classifies patients with CKD, with high sensitivity at 99.46%, accuracy at 99.26%, Specificity at 98%, F-score at 99.63%, and kappa value at 98.29%. The proposed system has many benefits including the fast transmission of medical data to the medical personnel, real-time tracking, and registration condition of the patient through a medical record. Potential enhancement of the performance measures the provider system’s hospital capacity and monitoring of a significant number of patients with a concentrated average delay.

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Section: Related Workmentioning

confidence: 99%

Smart Health Monitoring System with Wireless Networks to Detect Kidney Diseases

Rathee¹,

Vinmathi²,

Priya³

et al. 2022

Computational Intelligence and Neuroscience

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“…Alraja et.al. developed an integrated solution for users (data owners) of IoT applications to enhance privacy protection in events of private data sharing with a data consumer by calculating privacy risks associated with that specific sharing and comparing them to the benefits to-be received, providing a list of risks and recommendations to allow the user to take a pragmatic and informed decision [3]. The authors use an inference model, based on the Semantic Web and its supporting technologies (e.g., domain ontologies expressed using OWL) to allow the user to determine the privacy risks incurred when some personal data elements are shared with a data consumer.…”

Section: Privacy Compliancementioning

confidence: 99%

“…Several studies share the same underlying technologies to deliver their solutions, including OWL/ontologies (all studies), SWRL [10,15,16,25,38,39,46,[50][51][52], RDF [17,18,32,37,47,59], SPARQL [17,37,59], XACML [15,38,39,51,57], Jena [25,36,37,46], Semantic APIs/Web Services [9,36,37], and Internet of Things (IoT) devices [3,18,59]. It demonstrates the flexibility of SW tools to allow the implementation of security mechanisms to protect sensitive data and still enable the interoperability and integration of such data.…”

Section: Costa Lima Et Al / Security Approaches For Electronic Health...mentioning

confidence: 99%

“…Although the articles classified in the Interoperability Infrastructure category in this research may touch on those issues, they may represent a disincentive for the use of SW technologies to promote interoperability and semantic integration of health data due to the level of complexity involved in their implementation. In this sense, the development of a plug-and-play comprehensive solution that could be offered as a service by trusted and secure cloud computing providers, as suggested by Alraja et.al [3], could be a way to simplify the implementation of security mechanisms in SW contexts.…”

Section: General Recommendations and Opportunities For Future Researchmentioning

confidence: 99%

See 1 more Smart Citation

Security approaches for electronic health data handling through the Semantic Web: A scoping review

Lima

Alves

Bernardi

et al. 2023

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Integration of health information systems are crucial to advance the effective delivery of healthcare for individuals and communities across organizational boundaries. Semantic Web technologies may be used to connect, correlate, and integrate heterogeneous datasets spread over the internet. However, when working with sensitive data, such as health data, security mechanisms are needed. A scoping review of the literature was undertaken to provide a broad view of security mechanisms applied to, or along with, Semantic Web technologies that could allow its use with health data. Searches were conducted in the most relevant databases for the scope of this work. The findings were classified according to the main objective and features presented by each solution. Twenty-six studies were included in the review. They introduced mechanisms that addressed several security attributes, such as authentication, authorization, integrity, availability, confidentiality, privacy, and provenance. These mechanisms support access control frameworks, semantic and functional interoperability infrastructures, and privacy compliance solutions. The findings suggest that the application and use of Semantic Web technologies is still growing, with the healthcare area being particularly interested. The main security mechanisms for Semantic Web technologies, the key security attributes and properties, and the main gaps in the literature were identified, helping to understand the technical needs to mitigate the risks of handling personal health information over the Semantic Web. Also, this research has shown that complex and robust solutions are available to successfully address several security properties and features, depending on the context that the electronic health data is being managed.

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“…Embora os artigos classificados na categoria Infraestrutura de Interoperabilidade desta pesquisa possam tocar nessas questões, as soluções podem, ao mesmo tempo, representar um desestímulo ao uso de tecnologias da Web Semântica para promover a interoperabilidade e a integração semântica de dados de saúde, devido à complexidade envolvida. No entanto, o desenvolvimento de uma solução plug-and-play a ser oferecida como um serviço por provedores de computação em nuvem confiáveis e seguros, conforme sugerido por (ALRAJA et al, 2021), pode representar uma forma de simplificar a implementação de mecanismos de segurança na Web Semântica.…”

Section: Seleção Dos Estudosunclassified

Arquitetura e recursos computacionais para coleta, gestão e interoperabilidade de dados de tuberculose

Lima¹

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À minha esposa Raquel, pelos insights, pelas sábias orientações sobre a prática da pesquisa científica e todo o apoio incondicional; Aos meus pais, pela educação proporcionada, da qual me orgulho fortemente, e pelo sempre efetivo apoio à continuidade dos meus estudos.Aos meus grandes amigos Felipe Pellison, Filipe Bernardi e Francisco Júnior, que caminharam comigo durante todo o tempo e que, sem eles, os conceitos de colaboração e trabalho em equipe teriam de ser reinventados.Aos profissionais Rafael Galliez e Karla Gram, pelas dicas, ensinamentos e trocas de experiências que ajudaram a nortear as atividades desenvolvidas.Ao meu caríssimo coorientador, Prof. Rui Rijo, pelo acolhimento em todos os momentos e por estar sempre de braços abertos.Ao meu orientador, Prof. Domingos Alves, pela disponibilidade, pela supervisão recebida e por, principalmente, acreditar no potencial de seus alunos.Ao Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), pela atribuição da bolsa de Desenvolvimento Tecnológico e Industrial (DTI), Nível A, que permitiu a execução de atividades relacionadas a este projeto de pesquisa. Eu não tenho ídolos.Tenho admiração por trabalho, dedicação e competência.

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An integrated framework for privacy protection in IoT — Applied to smart healthcare

Cited by 14 publications

References 17 publications

Smart Health Monitoring System with Wireless Networks to Detect Kidney Diseases

Smart Health Monitoring System with Wireless Networks to Detect Kidney Diseases

Security approaches for electronic health data handling through the Semantic Web: A scoping review

Arquitetura e recursos computacionais para coleta, gestão e interoperabilidade de dados de tuberculose

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