AI-Powered Threat Intelligence: Revolutionizing Cybersecurity with Proactive Risk Management for Critical Sectors

The rapid evolution of cyber threats has necessitated a paradigm shift in cybersecurity strategies, particularly in critical sectors such as healthcare, finance, energy, and transportation. This paper explores the transformative role of AI-powered threat intelligence in revolutionizing cybersecurity practices. By leveraging advanced machine learning algorithms, natural language processing, and predictive analytics, AI-driven systems can detect, analyze, and mitigate threats with unprecedented speed and accuracy. This research highlights the integration of real-time data processing, threat intelligence platforms, and adaptive security frameworks to enable proactive risk management. Case studies and experimental results underscore the effectiveness of AI-powered approaches in anticipating cyberattacks, reducing response times, and minimizing operational disruptions. The findings demonstrate that AI is not merely a tool but a pivotal enabler of robust, adaptive, and scalable cybersecurity strategies in the face of an ever-evolving threat landscape.

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Publication Details

Journal
Journal of Artificial Intelligence General science (JAIGS) ISSN 3006-4023
Published
2024-12-19
DOI
https://doi.org/10.60087/jaigs.v7i01.291
Citations
15
Primary Topic
Information and Cyber Security
Type
article
Field-Weighted Citation Impact
11.69
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AI-Powered Threat Intelligence: Revolutionizing Cybersecurity with Proactive Risk Management for Critical Sectors

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Journal of Artificial Intelligence General science (JAIGS) ISSN 3006-4023
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AI-Powered Threat Intelligence: Revolutionizing Cybersecurity with Proactive Risk Management for Critical Sectors

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Abstract

The rapid evolution of cyber threats has necessitated a paradigm shift in cybersecurity strategies, particularly in critical sectors such as healthcare, finance, energy, and transportation. This paper explores the transformative role of AI-powered threat intelligence in revolutionizing cybersecurity practices. By leveraging advanced machine learning algorithms, natural language processing, and predictive analytics, AI-driven systems can detect, analyze, and mitigate threats with unprecedented speed and accuracy. This research highlights the integration of real-time data processing, threat intelligence platforms, and adaptive security frameworks to enable proactive risk management. Case studies and experimental results underscore the effectiveness of AI-powered approaches in anticipating cyberattacks, reducing response times, and minimizing operational disruptions. The findings demonstrate that AI is not merely a tool but a pivotal enabler of robust, adaptive, and scalable cybersecurity strategies in the face of an ever-evolving threat landscape.

Journal of Artificial Intelligence General science (JAIGS) ISSN 3006-4023Vol. 7(01)
Independent University, Bangladesh (BD), Science and Technology Corporation (United States) (US)
Openalex Percentile: Top 2%
Information and Cyber Security
11.69
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