JOURNAL ARTICLE

AI-augmented cyber security threat intelligence – enhancing situational awareness

Edim, Edim BasseyUdofot, Akpan ItoroOluseyi, Omotosho Moses

Year: 2025 Journal:   Zenodo (CERN European Organization for Nuclear Research)   Publisher: European Organization for Nuclear Research

Abstract

<p>In the evolving landscape of cyber threats, traditional threat intelligence methods are increasingly inadequate for addressing the complexity and speed of modern attacks. This paper explores the transformative impact of Artificial Intelligence (AI) on enhancing cyber security threat intelligence and situational awareness. By leveraging advanced AI technologies—such as machine learning, natural language processing, and data analytics—organizations can significantly improve their ability to detect, analyze, and respond to threats. We provide a comprehensive review of current AI applications in threat intelligence, illustrating how these technologies enable proactive threat management and enhance situational awareness. Through detailed case studies, we demonstrate the effectiveness of AI-driven solutions in various sectors, including finance and healthcare. The paper also addresses key challenges such as data privacy, system integration, and adversarial AI, offering recommendations for future research and development. This study underscores the critical role of AI in advancing cyber security practices and provides insights into how organizations can harness AI to achieve a more robust and responsive threat intelligence framework.</p>

Keywords:
Situation awareness Transformative learning Key (lock) Adversarial system Situational ethics Cyber threats Intelligence analysis

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