Stress Detection:Detecting, Monitoring, and Reducing Stress in Cyber-Security Operation Centers Using Facial Expression Recognition Software

74 Pages Posted: 8 May 2024

See all articles by Tiffany A. Davis Stewart

Tiffany A. Davis Stewart

North Carolina Agricultural and Technical State University

Abstract

The accessibility of technology and the IOT (Internet of Things) available at our fingertips, twenty-four hours per day, can quickly become a technological overload. For many reasons, this can be problematic for people working in front of computers, whether at home or in an office setting. Our “first responders” in cybersecurity, the analyst that works consistently in front of multiple computer screens and mobile devices to protect data from various forms of attacks are at a higher risk. Unmanaged stress can lead to poor job performance such as multiple health-related absences, missed warning signals on possible cyberattacks, and an overall lack of enthusiasm for the work needed to be done.

Keywords: Stress Stress DetectionCybersecurityIOTFacial Expression Recognition softwareAnxietyTechnologyMultimodelWearable BiosensorsEEGEKGGSR

Suggested Citation

Davis Stewart, Tiffany A., Stress Detection:Detecting, Monitoring, and Reducing Stress in Cyber-Security Operation Centers Using Facial Expression Recognition Software. Available at SSRN: https://ssrn.com/abstract=4820875 or http://dx.doi.org/10.2139/ssrn.4820875

Tiffany A. Davis Stewart (Contact Author)

North Carolina Agricultural and Technical State University ( email )

1601 E. Market St.
Greensboro, NC 27411
United States

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