Author
Abstract
The convergence of artificial intelligence, machine identities, and privileged access management represents a pivotal shift in the cybersecurity landscape, introducing unprecedented challenges for modern organizations. This comprehensive analysis examines how artificial intelligence-powered threats are revolutionizing attack vectors through automated social engineering, adaptive malware, and intelligent ransomware capabilities, while simultaneously transforming defensive strategies through enhanced threat detection and human-artificial intelligence collaboration. This article explores the critical intersection of machine identity proliferation - encompassing applications, containers, and Internet of Things devices - with traditional security frameworks, highlighting the complexities of certificate management, access controls, and continuous monitoring in automated environments. Furthermore, it investigates the evolution of privileged access management as it adapts to secure both human and machine identities, addressing challenges such as artificial intelligence-augmented privilege escalation and insufficient monitoring capabilities. Special attention is given to emerging trends, including artificial intelligence-driven attack simulation, unified identity and access management solutions, and evolving regulatory requirements, providing organizations with actionable insights for developing resilient security strategies in an increasingly complex digital ecosystem.
Suggested Citation
Sushant Chowdhary, 2025.
"Protecting the Digital Ecosystem: AI's Dual Role in Machine Identity Security,"
International Journal of Scientific Research in Computer Science, Engineering and Information Technology, International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 11(1), pages 1986-1996, February.
Handle:
RePEc:jbh:ijsrcs:v11:y2025:i1:id:864
DOI: 10.32628/CSEIT251112200
Note: Article URL: https://ijsrcseit.com/home/article/view/CSEIT251112200
Download full text from publisher
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:jbh:ijsrcs:v11:y2025:i1:id:864. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Pankaj Sharma (email available below). General contact details of provider: https://ijsrcseit.com/home .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.