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Secure and efficient WBANs algorithm with authentication mechanism

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  • معلومة اضافية
    • بيانات النشر:
      IOS Press, 2021.
    • الموضوع:
      2021
    • نبذة مختصرة :
      Due to the rapid growth in sensor technology and embedded technology, wireless body area network WBANs plays a vital role in monitoring the human body system and the surrounding environment. It supports many healthcare applications on the one hand and are very much help full in pandemic scenarios. It has become the most innovative health care area, which is intriguing to many researchers because of its vast future prospective and potential. Data collected by different wireless sensors or nodes is very personal, critical, and important because of human life involvement. WBANs can minimize human to human contact, which helps stop the spread of severe infectious diseases. The biggest concern is the maintenance of privacy and accuracy of data is still a hot area of research due to nature of attacks, which are changing day by day and increasing, as well as for the sake of better performance. A suitable security mechanism is a way to address above issues, for achieving data security, it is expedient to propose a mechanism. It is essential to update the patient’s regular data. WBANs help to deliver truthful reports related to the patient’s health regularly and individually. This paper proposes an algorithm that shows a better result than the existing algorithm in their previous works. This work is all about proposing a mechanism which needs comparatively less resource. Only authentic entities can interact with the server, which has become obligatory for both sides, keeping data safe. Several authentication schemes have been proposed or discussed by different researchers. This paper has proposed a Secure and Efficient WBANs Authentication Mechanism (SEAM). This security framework will take care of the authentication and the security of transmitted data.
    • ISSN:
      1875-8967
      1064-1246
    • الرقم المعرف:
      edsair.doi...........e32720f49dda17f89c5147178aedf95e