IDEAS home Printed from https://ideas.repec.org/a/epw/ejeng0/v8y2023i4id63064.html

Enhancing Security for Robot-Assisted Surgery through Advanced Authentication Mechanisms Over 5G Networks

Author

Listed:
  • Shaman Bhat

    (Qualcomm Technologies Inc., USA)

  • Ashwin Kavasseri

    (University of Cincinnati, USA)

Abstract

The adoption of robotic surgical procedures over wireless 5G networks has increased rapidly in recent years, providing improved precision and patient outcomes. However, the security and reliability of the end-to-end information between the surgeon's control console and the robotic system are critical concerns. This paper proposes a solution to enhance the security and reliability of the authentication process in robot-assisted surgery by enhancing existing authentication mechanisms. The proposed solution builds upon the existing Transport Layer Security (TLS) protocol, and introduces additional security measures, including biometric authentication and multi-factor authentication while minimizing latency and delay in transmission. The effectiveness of the proposed solution is evaluated through simulation and testing, demonstrating its ability to provide enhanced security for robot-assisted surgery. The proposed solution has the potential to provide an additional layer of security while staying in realistic bounds of latency and delay in data transmission.

Suggested Citation

  • Shaman Bhat & Ashwin Kavasseri, 2023. "Enhancing Security for Robot-Assisted Surgery through Advanced Authentication Mechanisms Over 5G Networks," European Journal of Engineering and Technology Research, European Open Science, vol. 8(4), pages 1-4, July.
    • Handle: RePEc:epw:ejeng0:v:8:y:2023:i:4:id:63064
    DOI: 10.24018/ejeng.2023.8.4.3064
    as

    Download full text from publisher

    File URL: https://eu-opensci.org/index.php/ejeng/article/view/63064
    File Function: Abstract page
    Download Restriction: no
    File URL: https://eu-opensci.org/index.php/ejeng/article/download/63064/12935
    File Function: Full text
    Download Restriction: no
    File URL: https://libkey.io/10.24018/ejeng.2023.8.4.3064?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:epw:ejeng0:v:8:y:2023:i:4:id:63064. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Support (email available below). General contact details of provider: https://eu-opensci.org/index.php/ejeng .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.