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

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.

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Publication Details

Journal
Cyber security.
Published
2024-08-11
DOI
https://doi.org/10.69554/sonj8694
Primary Topic
Personal Information Management and User Behavior
Type
article
Field-Weighted Citation Impact
0.00
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article

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

Sarah Katz
Cyber security.
Personal Information Management and User Behavior
article

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

Sarah Katz
article en

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.

Cyber security.Vol. 8(1)
Microsoft (Germany) (DE)
Openalex Percentile: Top 86%
Personal Information Management and User Behavior
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