AI-Driven Threat Intelligence for Proactive Cybersecurity in Enterprise Networks

Today, new and advanced attacks arise and for this reason, effective mechanisms for the protection of enterprise networks must be developed. AI based threat intelligence systems provide the feature of continuous monitoring, big data analytics and prediction that helps to improve proactive security. This paper focus on the application of AI in threat identification, abnormality identification and response Automation with an aim of illustrating their roles in the prevention of emerging new threats. Thereby, the study identifies current trends in enterprise cybersecurity and provide case studies to show how AI-based cybersecurity frameworks can help organisations adopt a strong and dynamic security stance against sophisticated cyber threats.

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Publication Details

Published
2025-05-29
DOI
https://doi.org/10.1109/netcrypt65877.2025.11102400
Citations
8
Primary Topic
Chaos-based Image/Signal Encryption
Type
article
Field-Weighted Citation Impact
10.21
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article

AI-Driven Threat Intelligence for Proactive Cybersecurity in Enterprise Networks

Rajneesh Kler, Kapil Jairath, Manik Rakhra, Gaurav Aggarwal et al.
8 citations
Chaos-based Image/Signal Encryption
10.21
article

AI-Driven Threat Intelligence for Proactive Cybersecurity in Enterprise Networks

Rajneesh Kler, Kapil Jairath, Manik Rakhra, Gaurav Aggarwal, Danish Ather, Amanpreet Singh
article en
8 citations

Abstract

Today, new and advanced attacks arise and for this reason, effective mechanisms for the protection of enterprise networks must be developed. AI based threat intelligence systems provide the feature of continuous monitoring, big data analytics and prediction that helps to improve proactive security. This paper focus on the application of AI in threat identification, abnormality identification and response Automation with an aim of illustrating their roles in the prevention of emerging new threats. Thereby, the study identifies current trends in enterprise cybersecurity and provide case studies to show how AI-based cybersecurity frameworks can help organisations adopt a strong and dynamic security stance against sophisticated cyber threats.

Lovely Professional University (IN)
Openalex Percentile: Top 2%
Chaos-based Image/Signal Encryption
10.21
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AI-Driven Threat Intelligence for Proactive Cybersecurity in Enterprise Networks — Rajneesh Kler, Kapil Jairath, et al. · (2025) | TGRS Research Map | TGRS