THE ROLE OF AI IN DETECTING INSIDER THREATS IN HEALTHCARE ORGANIZATIONS

This article explores the critical role of Artificial Intelligence (AI) in detecting and preventing insider threats within healthcare organizations. It examines the growing challenges of data security in the healthcare sector, highlighting the significant financial and reputational risks posed by insider threats. The article discusses various types of insider threats, including malicious actors, negligent employees, and compromised credentials. It then delves into how AI enhances insider threat detection through behavioral analytics, machine learning, natural language processing, and predictive analytics. The article outlines key steps for implementing AI-based insider threat detection systems and addresses the ethical considerations and privacy concerns associated with such implementations. By leveraging AI technologies, healthcare organizations can significantly improve their ability to protect sensitive patient data and maintain the integrity of their systems.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-10-21
DOI
https://doi.org/10.5281/zenodo.13960643
Citations
1
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.12
Controls
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article

THE ROLE OF AI IN DETECTING INSIDER THREATS IN HEALTHCARE ORGANIZATIONS

1 citations
Zenodo (CERN European Organization for Nuclear Research)
Artificial Intelligence in Healthcare and Education
0.12
article

THE ROLE OF AI IN DETECTING INSIDER THREATS IN HEALTHCARE ORGANIZATIONS

article en
1 citations

Abstract

This article explores the critical role of Artificial Intelligence (AI) in detecting and preventing insider threats within healthcare organizations. It examines the growing challenges of data security in the healthcare sector, highlighting the significant financial and reputational risks posed by insider threats. The article discusses various types of insider threats, including malicious actors, negligent employees, and compromised credentials. It then delves into how AI enhances insider threat detection through behavioral analytics, machine learning, natural language processing, and predictive analytics. The article outlines key steps for implementing AI-based insider threat detection systems and addresses the ethical considerations and privacy concerns associated with such implementations. By leveraging AI technologies, healthcare organizations can significantly improve their ability to protect sensitive patient data and maintain the integrity of their systems.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 44%
Artificial Intelligence in Healthcare and Education
0.12
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THE ROLE OF AI IN DETECTING INSIDER THREATS IN HEALTHCARE ORGANIZATIONS · Zenodo (CERN European Organization for Nuclear Research) (2024) | TGRS Research Map | TGRS