IDEAS home Printed from https://ideas.repec.org/a/aza/csj000/y2024v8i1p38-47.html
   My bibliography  Save this article

AI detection of malicious push notifications in augmented reality in the workplace

Author

Listed:
  • Katz, Sarah

    (Cybersecurity Technical Writer, Microsoft, USA)

Abstract

Distraction caused by the visual processing of multiple objects during augmented reality (AR) immersion could make users more susceptible to malicious push notifications, thus potentially exposing organisations to unwitting insider threats. This case study consulted four experts in the field of AR application development to design a proposed artificial intelligence (AI) equipped feature that could detect possibly malicious artefacts entering the user’s line of sight during partial immersion in an augmented reality application at the workplace. Participants included a business partner at an AR company, a security engineering manager, an AI engineer focused on machine learning (ML) and a data analytics specialist. The case study determined that a security application natively implemented into the device could use heuristic analysis of user screen captured activity to assess potentially malicious push notifications in real time.

Suggested Citation

  • Katz, Sarah, 2024. "AI detection of malicious push notifications in augmented reality in the workplace," Cyber Security: A Peer-Reviewed Journal, Henry Stewart Publications, vol. 8(1), pages 38-47, September.
    • Handle: RePEc:aza:csj000:y:2024:v:8:i:1:p:38-47
    as

    Download full text from publisher

    File URL: https://hstalks.com/article/8631/download/
    Download Restriction: Requires a paid subscription for full access.
    File URL: https://hstalks.com/article/8631/
    Download Restriction: Requires a paid subscription for full access.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    More about this item

    Keywords

    cyber security; cyberpsychology; augmented reality; application development; artificial intelligence;
    All these keywords.

    JEL classification:

    • M15 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - IT Management

    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:aza:csj000:y:2024:v:8:i:1:p:38-47. 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: Henry Stewart Talks (email available below). General contact details of provider: .

    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.