AI-Driven Threat Detection and Response

Authors

  • Pietro Di Maria GM & Co-Founder, Meridian Group | Assoc. Researcher, EDHEC Business School, Italy Author

DOI:

https://doi.org/10.47363/JAICC/ICAIC2025/2025(4)5

Keywords:

AI-Driven, Detection

Abstract

The increasing sophistication of the cyber threat landscape demands a systemic and cross-disciplinary approach that integrates 
Cyber Threat Intelligence (CTI) with Competitive Intelligence (CI). Traditional cybersecurity measures, often focused on detection 
and incident response, are no longer sufficient in environments characterized by asymmetrical threats, geopolitical tensions, and 
rapid technological change. To address these challenges, Kitsune (Meridian Group) has developed an operational model that 
merges CTI methodologies with CI practices, creating a comprehensive knowledge ecosystem designed to identify weak signals, 
anticipate emerging risks, and inform strategic decision-making processes. The proposed framework is structured along three key 
dimensions. First, data collection and enrichment, combining heterogeneous sources such as OSINT, HUMINT, technical feeds, 
and commercial intelligence, which are normalized and enriched to ensure interoperability and actionable insights. Second, multi
level threat analysis, spanning from the identification of indicators of compromise (IoCs) and adversary tactics, techniques, and 
procedures (TTPs) mapped to MITRE ATT&CK, to the evaluation of strategic risks related to state actors, cybercriminal groups, 
and geopolitical drivers. Third, competitive contextualization, where cyber threat insights are correlated with sectoral dynamics, 
business risks, and market trends, enabling organizations to transform threat intelligence into a lever of decision advantage. The 
integration of machine learning and predictive analytics further enhances the framework, enabling the identification of recurring 
patterns and advanced persistent threats (APTs), while simultaneously improving prevention, detection, and resilience. This 
convergence ensures that decision makers benefit from situational awareness not only in the cyber domain but also across strategic 
and competitive contexts. Such awareness allows for the optimization of cybersecurity investments, prioritization of defensive 
capabilities, and the proactive anticipation of market and reputational risks tied to the evolving threat environment. Empirical 
results from the Kitsune model indicate that the convergence of CTI and CI delivers dual value. On the one hand, it strengthens the 
organization? s ability to detect and mitigate threats in near real-time, reducing operational exposure and the potential impact of 
attacks. On the other hand, it fosters long-term resilience by embedding intelligence-driven perspectives into corporate strategy, risk 
management, and governance frameworks. This contribution aims to stimulate discussion on the necessity of bridging technical and 
strategic intelligence practices, highlighting how the integration of CTI and CI is increasingly becoming a differentiator in complex 
operating environments. By positioning cybersecurity not as a purely technical safeguard but as a strategic and competitive enabler, 
organizations can better navigate uncertainty, protect critical assets, and sustain a competitive advantage in the digital age.

Author Biography

  • Pietro Di Maria, GM & Co-Founder, Meridian Group | Assoc. Researcher, EDHEC Business School, Italy

    Pietro Di Maria, GM & Co-Founder, Meridian Group | Assoc. Researcher, EDHEC Business School, Italy

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Published

2026-11-28

How to Cite

AI-Driven Threat Detection and Response. (2026). Journal of Artificial Intelligence & Cloud Computing, 4(6), 1-1. https://doi.org/10.47363/JAICC/ICAIC2025/2025(4)5

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