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Optimal Distributed Generator Sizing and Placement by Modified Particle Swarm Optimization (MPOS) Algorithm for Minimization of Distribution Power Loss

Anshu Sharma Rajesh Kumar Rai Ghizal Ansari
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AI-Driven Solutions for Enhancing Cybersecurity in Healthcare Systems: A Comprehensive Review

by Thangaraj Petchiappan
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Journal of Advanced Artificial Intelligence
Foundation of Computer Science (FCS), NY, USA
Volume 1 - Number 7
Year of Publication: 2025
Authors: Thangaraj Petchiappan
10.5120/jaai202435

Thangaraj Petchiappan . AI-Driven Solutions for Enhancing Cybersecurity in Healthcare Systems: A Comprehensive Review. Journal of Advanced Artificial Intelligence. 1, 7 ( Jun 2025), 1-8. DOI=10.5120/jaai202435

@article{ 10.5120/jaai202435,
author = { Thangaraj Petchiappan },
title = { AI-Driven Solutions for Enhancing Cybersecurity in Healthcare Systems: A Comprehensive Review },
journal = { Journal of Advanced Artificial Intelligence },
issue_date = { Jun 2025 },
volume = { 1 },
number = { 7 },
month = { Jun },
year = { 2025 },
pages = { 1-8 },
numpages = {9},
url = { https://jaaionline.phdfocus.com/archives/volume1/number7/ai-driven-solutions-for-enhancing-cybersecurity-in-healthcare-systems-a-comprehensive-review/ },
doi = { 10.5120/jaai202435 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2025-06-30T14:35:41+05:30
%A Thangaraj Petchiappan
%T AI-Driven Solutions for Enhancing Cybersecurity in Healthcare Systems: A Comprehensive Review
%J Journal of Advanced Artificial Intelligence
%V 1
%N 7
%P 1-8
%D 2025
%I Foundation of Computer Science (FCS), NY, USA
Abstract

As healthcare businesses face more and more cyber hazards as a result of digital technology's increasing integration into healthcare systems, cybersecurity is taking on more significance. This analysis looks at how AI may improve cybersecurity in the healthcare industry. AI technologies, such as ML, DL, and NLP, have become effective instruments for identifying, evaluating, and reducing cyber threats. The study demonstrates the efficacy of AI applications in cybersecurity, including automated incident response, anomaly detection, and predictive maintenance, in protecting sensitive patient data and guaranteeing the provision of essential healthcare services. Additionally, a paper discusses the regulatory frameworks that govern healthcare data security, including HIPAA and GDPR, which further emphasize the need for robust cybersecurity solutions. By exploring the current landscape of AI-driven cybersecurity challenges with solutions, this review aims to provide insights into best practices, emerging trends, and future directions for research and implementation in healthcare cybersecurity.

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Index Terms

Computer Science
Information Sciences

Keywords

Cybersecurity and AI-driven solutions in cybersecurity AI-driven solutions for Cybersecurity in Healthcare Systems Challenges.

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