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Real-Time Remote Health Monitoring Systems Using Body Sensor Information and Finger Vein Biometric Verification: A Multi-Layer Systematic Review

机译:使用身体传感器信息和手指静脉生物识别的实时远程健康监控系统:多层系统评论

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The development of wireless body area sensor networks is imperative for modern telemedicine. However, attackers and cybercriminals are gradually becoming aware in attacking telemedicine systems, and the black market value of protected health information has the highest price nowadays. Security remains a formidable challenge to be resolved. Intelligent home environments make up one of the major application areas of pervasive computing. Security and privacy are the two most important issues in the remote monitoring and control of intelligent home environments for clients and servers in telemedicine architecture. The personal authentication approach that uses the finger vein pattern is a newly investigated biometric technique. This type of biometric has many advantages over other types (explained in detail later on) and is suitable for different human categories and ages. This study aims to establish a secure verification method for real-time monitoring systems to be used for the authentication of patients and other members who are working in telemedicine systems. The process begins with the sensor based on Tiers 1 and 2 (client side) in the telemedicine architecture and ends with patient verification in Tier 3 (server side) via finger vein biometric technology to ensure patient security on both sides. Multilayer taxonomy is conducted in this research to attain the study's goal. In the first layer, real-time remote monitoring studies based on the sensor technology used in telemedicine applications are reviewed and analysed to provide researchers a clear vision of security and privacy based on sensors in telemedicine. An extensive search is conducted to identify articles that deal with security and privacy issues, related applications are reviewed comprehensively and a coherent taxonomy of these articles is established. ScienceDirect, IEEE Xplore and Web of Science databases are checked for articles on mHealth in telemedicine based on sensors. A total of 3064 papers are collected from 2007 to 2017. The retrieved articles are filtered according to the security and privacy of telemedicine applications based on sensors. Nineteen articles are selected and classified into two categories. The first category, which accounts for 57.89% (n=11/19), includes surveys on telemedicine articles and their applications. The second category, accounting for 42.1% (n=8/19), includes articles on the three-tiered architecture of telemedicine. The collected studies reveal the essential need to construct another taxonomy layer and review studies on finger vein biometric verification systems. This map-matching for both taxonomies is developed for this study to go deeply into the sensor field and determine novel risks and benefits for patient security and privacy on client and server sides in telemedicine applications. In the second layer of our taxonomy, the literature on finger vein biometric verification systems is analysed and reviewed. In this layer, we obtain a final set of 65 articles classified into four categories. In the first category, 80% (n=52/65) of the articles focus on development and design. In the second category, 12.30% (n=8/65) includes evaluation and comparative articles. These articles are not intensively included in our literature analysis. In the third category, 4.61% (n=3/65) includes articles about analytical studies. In the fourth category, 3.07% (n=2/65) comprises reviews and surveys.
机译:无线体积传感器网络的开发是现代远程杂种的势在必行。然而,攻击者和网络犯罪分子在攻击远程医疗系统中逐渐变得意识到受保护健康信息的黑市价值现在具有最高的价格。安全性仍然是一个强大的挑战。智能家居环境构成普遍计算的主要应用领域之一。安全性和隐私是远程监控和控制远程模型架构中客户端和服务器的远程监控和控制的两个最重要的问题。使用手指静脉模式的个人认证方法是一种新的研究生物识别技术。这种类型的生物识别具有与其他类型的许多优点(稍后详细解释)并且适用于不同的人类类别和年龄。本研究旨在建立一个安全的验证方法,用于用于患者认证和在远程医疗系统中的患者身份认证和其他成员的实时监测系统。该过程基于远程医疗架构中的Tiers 1和2(客户端)的传感器开始,并通过手指静脉生物识别技术在Tier 3(服务器侧)中的患者验证结束,以确保两侧的患者安全性。多层分类法在这项研究中进行,以获得研究的目标。在第一层中,综述并分析了基于远程医疗应用中使用的传感器技术的实时远程监测研究,并为研究人员提供了基于远程医疗传感器的安全和隐私的清晰愿景。进行了广泛的搜索,以确定处理安全和隐私问题的文章,全面审查相关申请,并建立了这些文章的一致性分类。基于传感器的远程医疗中的MHEALTINES检查SCIERDERCINECT,IEEE XPLORE和科学数据库网站。从2007年至2017年收集了共有3064篇论文。根据传感器的远程医疗应用的安全和隐私,检索到的文章得到过滤。选择并分为两类文章。第一个类别,占57.89%(n = 11/19),包括在远程医疗文章及其申请上调查。第二类,占42.1%(n = 8/19),包括关于远程医疗的三层建筑的文章。收集的研究揭示了构建另一个分类层的必要必要性,并对手指静脉生物识别系统进行审查研究。这张地图匹配的两种分类都是为本研究开发的,以深入进入传感器字段,并确定远程医疗应用程序中的客户端和服务器边的患者安全和隐私的新型风险和益处。在我们分类的第二层,分析并审查了手指静脉生物识别系统的文献。在这层中,我们获得了分为四类的最终65篇文章。在第一类,80%(n = 52/65)的文章专注于开发和设计。在第二类中,12.30%(n = 8/65)包括评估和比较制品。这些文章在我们的文献分析中没有集中纳入。在第三类中,4.61%(n = 3/65)包括关于分析研究的文章。在第四类,3.07%(n = 2/65),包括审查和调查。

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