Leveraging AI-Enhanced IAM, PAM, and IGA for Cybersecurity: A Cross-Industry Approach to Reducing Cyber Attacks

The rapid advancement of artificial intelligence (AI) has significantly impacted the cybersecurity landscape, particularly in the domains of Identity and Access Management (IAM), Privileged Access Management (PAM), and Identity Governance and Administration (IGA). These technologies are critical for controlling and monitoring access to sensitive systems and data within organizations. AI enhances traditional IAM, PAM, and IGA systems by introducing automation, predictive analytics, and real-time decision-making, allowing organizations to proactively manage access controls, detect threats, and ensure compliance with regulatory standards.This paper explores the evolution and role of AI in enhancing cybersecurity across various industries, highlighting key benefits such as improved threat detection, reduced human error, and streamlined compliance processes. It examines how AI transforms traditional static security measures into adaptive, intelligent systems capable of dynamically responding to emerging risks. Additionally, the paper discusses challenges such as data privacy concerns, integration complexities, and the need for specialized talent.Looking forward, the future of AI in IAM, PAM, and IGA holds exciting possibilities, including autonomous access management, enhanced predictive security, and stronger integrations with technologies like blockchain. These innovations promise to further strengthen organizations' security postures, enabling them to effectively combat increasingly sophisticated cyber threats.

Authors

Publication Details

Journal
Journal of Information Systems Engineering & Management
Published
2025-03-06
DOI
https://doi.org/10.52783/jisem.v10i16s.2568
Primary Topic
Adversarial Robustness in Machine Learning
Type
article
Field-Weighted Citation Impact
0.00
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article

Leveraging AI-Enhanced IAM, PAM, and IGA for Cybersecurity: A Cross-Industry Approach to Reducing Cyber Attacks

Surendra Vitla
Journal of Information Systems Engineering & Management
Adversarial Robustness in Machine Learning
article

Leveraging AI-Enhanced IAM, PAM, and IGA for Cybersecurity: A Cross-Industry Approach to Reducing Cyber Attacks

Surendra Vitla
article en

Abstract

The rapid advancement of artificial intelligence (AI) has significantly impacted the cybersecurity landscape, particularly in the domains of Identity and Access Management (IAM), Privileged Access Management (PAM), and Identity Governance and Administration (IGA). These technologies are critical for controlling and monitoring access to sensitive systems and data within organizations. AI enhances traditional IAM, PAM, and IGA systems by introducing automation, predictive analytics, and real-time decision-making, allowing organizations to proactively manage access controls, detect threats, and ensure compliance with regulatory standards.This paper explores the evolution and role of AI in enhancing cybersecurity across various industries, highlighting key benefits such as improved threat detection, reduced human error, and streamlined compliance processes. It examines how AI transforms traditional static security measures into adaptive, intelligent systems capable of dynamically responding to emerging risks. Additionally, the paper discusses challenges such as data privacy concerns, integration complexities, and the need for specialized talent.Looking forward, the future of AI in IAM, PAM, and IGA holds exciting possibilities, including autonomous access management, enhanced predictive security, and stronger integrations with technologies like blockchain. These innovations promise to further strengthen organizations' security postures, enabling them to effectively combat increasingly sophisticated cyber threats.

Journal of Information Systems Engineering & ManagementVol. 10(16s)
Openalex Percentile: Top 98%
Adversarial Robustness in Machine Learning
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