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

S A Mohaiminul Islam (), Shadikul Bari Md (), Ankur Sarkar (), A J M Obaidur Rahman Khan () and Rakesh Paul ()

Journal of Artificial Intelligence General science (JAIGS) ISSN:3006-4023, 2024, vol. 7, issue 01, 1-8

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.

Keywords: AI-powered threat intelligence; cybersecurity; proactive risk management; critical sectors; machine learning; real-time threat detection; adaptive security; predictive analytics (search for similar items in EconPapers)
Date: 2024
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Citations: View citations in EconPapers (5)

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