NYU Open Research : Scholarly materials produced by members of the NYU community.
Published October 9, 2024 | Version v1
Preprint Open

Enhancing Insider Threat Detection: A Literature Review on AI-Driven Solutions Leveraging Wearable Technology

  • 1. ROR icon New York University

Description

This literature review explores the landscape of AI-driven insider threat detection leveraging wearable technology. Insider threats pose significant risks to organizations, often stemming from trusted individuals with access to sensitive information. Traditional security measures focus primarily on external threats, overlooking the potential dangers posed by insiders. By integrating wearable technology with advanced AI algorithms, organizations can enhance their ability to detect and mitigate insider threats in real-time. This paper examines existing research, methodologies, and technologies employed in the domain of insider threat detection, with a specific emphasis on the role of wearable devices and AI-driven approaches. Insights gained from this review contribute to a deeper understanding of effective strategies for safeguarding against insider threats.

Files

r6w87-k8r78.pdf

Files (451.8 kB)

Name Size Download all
r6w87-k8r78.pdf md5:53800569ae79b105f73c6216d65f47b1
451.8 kB Preview Download