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A joint resource-aware and medical data security framework for wearable healthcare systems

机译:可穿戴医疗保健系统的联合资源感知和医疗数据安全框架

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摘要

Internet of Medical Things (IoMTs) is a building block for modern healthcare having enormously stringent resource constraints thus lightweight health data security and privacy are crucial requirements. A critical issue in implementing security for the streaming health information is to offer data privacy and validation of a patient's information over networking environment in a resource efficient manner. Therefore, we developed a biometric-based security framework for resource-constrained wearable health monitoring systems by extracting heartbeats from ECG signals. It is analyzed that time-domain based biometric features play a significant role in optimizing security in IoMT based medical applications. Moreover, resource optimization model based on utility function is proposed for clinical information transmission in loMT. In this study, ECG signals from 40 healthy subjects were employed comprising lab environment and publicly available database i-e-physionet. The experimental results validate that proposed framework requires less processing time and energy consumption (0.0068ms and 0.196 microJoule/Byte) then Alarmnet (0.0128ms and 0.351 microJoule/Byte) and BSN-care (0.0175ms and 0.53 microJoule/Byte). Moreover, from the results, it is also observed that biometric key generation mechanism not only provide random and unique keys but it also offer a trade-off between security and resource optimization. Thus, it can be concluded that the proposed framework has got both social and economic significance for real-time healthcare applications. (C) 2019 Elsevier B.V. All rights reserved.
机译:医疗互联网(IOMTS)是现代医疗保健的建筑块,具有极大严格的资源限制,因此轻量级的健康数据安全性和隐私是至关重要的要求。实施流媒体健康信息安全性的关键问题是以资源有效的方式为患者提供患者信息的数据隐私和验证患者信息。因此,我们通过从ECG信号中提取心跳来开发了一种基于生物识别的可穿戴健康监测系统的安全框架。分析了基于时域的生物识别功能在优化基于IOMT的医疗应用中的安全性方面发挥着重要作用。此外,提出了基于公用事业功能的资源优化模型,用于LOMT中的临床信息传输。在这项研究中,从40名健康受试者的ECG信号被雇用包括实验室环境和可公开获得的数据库I-E-physionet。实验结果验证了所提出的框架需要较少的处理时间和能量消耗(0.0068ms和0.196微joule / byte),然后是Alarmnet(0.0128ms和0.351微joule / byte)和BSN-care(0.0175ms和0.53微joule / byte)。此外,从结果中,还观察到生物识别密钥生成机制不仅提供随机和唯一的键,而且还提供了安全性和资源优化之间的权衡。因此,可以得出结论,拟议的框架对实时医疗保健应用具有社会和经济意义。 (c)2019 Elsevier B.v.保留所有权利。

著录项

  • 来源
    《Future generation computer systems》 |2019年第6期|382-391|共10页
  • 作者单位

    Shenzhen Inst Adv Technol CAS Key Lab Human Machine Intelligence Synergy Sy Shenzhen 518055 Peoples R China|Chinese Acad Sci SIAT Inst Biomed & Hlth Engn Shenzhen 518055 Peoples R China|Univ Chinese Acad Sci Shenzahen Coll Adv Technol Shenzhen 518055 Peoples R China;

    Shenzhen Inst Adv Technol CAS Key Lab Human Machine Intelligence Synergy Sy Shenzhen 518055 Peoples R China|Chinese Acad Sci SIAT Inst Biomed & Hlth Engn Shenzhen 518055 Peoples R China|Univ Chinese Acad Sci Shenzahen Coll Adv Technol Shenzhen 518055 Peoples R China;

    Shenzhen Inst Adv Technol CAS Key Lab Human Machine Intelligence Synergy Sy Shenzhen 518055 Peoples R China|Chinese Acad Sci SIAT Inst Biomed & Hlth Engn Shenzhen 518055 Peoples R China;

    VIT Univ Sch Comp Sci & Engn Vellore 632014 Tamil Nadu India;

    Shenzhen Inst Adv Technol CAS Key Lab Human Machine Intelligence Synergy Sy Shenzhen 518055 Peoples R China|Chinese Acad Sci SIAT Inst Biomed & Hlth Engn Shenzhen 518055 Peoples R China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Healthcare; Data security; Patient's privacy; Resource-efficient; Internet of Medical Things;

    机译:医疗保健;数据安全;患者的隐私;资源效率;医学互联网;

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