AI in Network Security: Enhancing Protection in the Age of Automation

This comprehensive article explores the transformative role of artificial intelligence in network security, addressing the evolving challenges and solutions in contemporary cybersecurity landscapes. The article delves into how AI-driven systems revolutionize threat detection, response capabilities, and security operations across organizations. Through analysis of machine learning algorithms, automated response systems, and emerging technologies, this article investigates the implementation challenges, best practices, and future considerations in AI security adoption. The article examines the impact of quantum computing, edge processing, and 5G networks on security paradigms while considering the complexities of data privacy, compliance requirements, and operational hurdles. This article provides insights into strategic planning, technical integration, and governance frameworks necessary for successful AI security implementation while exploring how organizations can prepare for future security challenges in an increasingly connected world.

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Publication Details

Journal
International Journal of Scientific Research in Computer Science Engineering and Information Technology
Published
2024-11-28
DOI
https://doi.org/10.32628/cseit241061146
Primary Topic
Network Security and Intrusion Detection
Type
article
Field-Weighted Citation Impact
0.00
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article

AI in Network Security: Enhancing Protection in the Age of Automation

Ramanathan Sekkappan
International Journal of Scientific Research in Computer Science Engineering and Information Technology
Network Security and Intrusion Detection
article

AI in Network Security: Enhancing Protection in the Age of Automation

Ramanathan Sekkappan
article en

Abstract

This comprehensive article explores the transformative role of artificial intelligence in network security, addressing the evolving challenges and solutions in contemporary cybersecurity landscapes. The article delves into how AI-driven systems revolutionize threat detection, response capabilities, and security operations across organizations. Through analysis of machine learning algorithms, automated response systems, and emerging technologies, this article investigates the implementation challenges, best practices, and future considerations in AI security adoption. The article examines the impact of quantum computing, edge processing, and 5G networks on security paradigms while considering the complexities of data privacy, compliance requirements, and operational hurdles. This article provides insights into strategic planning, technical integration, and governance frameworks necessary for successful AI security implementation while exploring how organizations can prepare for future security challenges in an increasingly connected world.

International Journal of Scientific Research in Computer Science Engineering and Information TechnologyVol. 10(6)
Madurai Kamaraj University (IN)
Openalex Percentile: Top 75%
Network Security and Intrusion Detection
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