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Authentication in Wireless Body Area Networks (WBAN).

机译:无线体域网(WBAN)中的身份验证。

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摘要

With the advancements in technology and computing environment capabilities, the number of devices that people carry has increased exponentially. This increase initially occurred as a result of necessity to monitor the human body condition due to chronic diseases, heart problems etc. Later, individuals' interest was drawn towards self-monitoring their physiology and health care. This is achieved by implanting various sensors that can proactively monitor the human body based on medical necessity and the health condition of the user. Sensors connected on a human body perceive phenomena such as locomotion or heartbeat, and act accordingly to form a Body Area Network. The primary concern of these sensors is to ensure a secure way of communication and coordination among the devices to form a flawless system. A secondary concern is wireless sensor authentication, which ensures trustworthiness and reliable gathering of a user's data. To address this concern, we designed a secure approach using low cost accelerometers to authenticate sensors in Body Area Networks.;To ensure authentication in on-body sensor networks, we need a mechanism which intuitively proves all the communicating nodes are trusted ones. In order to achieve sensor authentication, we used accelerometer data gathered from sensors to distinguish whether or not the devices are carried on waist of same individual's body. Our approach is focused at analyzing walking patterns recorded from smartphone accelerometers placed in the same location of the user's body, and we present results showing these sensors record similar pattern.
机译:随着技术和计算环境功能的进步,人们携带的设备数量呈指数增长。这种增加最初是由于必须监测由于慢性疾病,心脏病等引起的人体状况而引起的。后来,人们对自我监测其生理和卫生保健产生了兴趣。这是通过植入各种传感器来实现的,这些传感器可以根据医疗需要和用户的健康状况主动监控人体。连接在人体上的传感器会感知运动或心跳等现象,并据此采取行动以形成人体局域网。这些传感器的主要考虑是确保设备之间通信和协调的安全方式,以形成一个完美的系统。第二个问题是无线传感器身份验证,它可以确保用户数据的可信度和可靠收集。为了解决这个问题,我们设计了一种安全的方法,使用低成本的加速度计来对人体局域网中的传感器进行身份验证。为了确保在人体传感器网络中进行身份验证,我们需要一种机制来直观地证明所有通信节点都是受信任的节点。为了实现传感器认证,我们使用从传感器收集的加速度计数据来区分设备是否携带在同一个人的腰部。我们的方法专注于分析从放置在用户身体相同位置的智能手机加速度计记录的行走模式,并且我们给出的结果表明这些传感器记录了相似的模式。

著录项

  • 作者

    Yenuganti, Nagalaxmi.;

  • 作者单位

    University of South Florida.;

  • 授予单位 University of South Florida.;
  • 学科 Computer science.
  • 学位 M.S.C.S.
  • 年度 2016
  • 页码 41 p.
  • 总页数 41
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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