SYSTEMATIC REVIEW OF THE PROBLEMS AND OPPORTUNITIES OF ARTIFICIAL INTELLIGENCE INCORPORATION WITH CYBER THREAT INTELLIGENCE SHARING, THREAT HUNTING, AND THREAT MODELING

Abstract

The rapid evolution of AI-powered cyberattacks has revolutionized the environment of cybersecurity, with adversaries using the means of automation of sophisticated attacks, which are beyond the capabilities of the existing cybersecurity environment. The estimated amount of cybercrimes in the world is $10.5 trillion annually, with an average cost of a data breach to an organization being $4.45 million. The existing cybersecurity environment is not sufficient, as it is not scalable, quick, and intelligent enough to combat the increasing number of cyberattacks. The biggest challenge in the context of the use of AI in the CTI environment is the lack of awareness and understanding of cybersecurity professionals/organizations about the use of artificial intelligence in CTI sharing, threat hunting, and threat modeling. The paper applied a systematic review of the literature available in the context of the last five years (2020-2026) from IEEE Xplore, ScienceDirect, ACM Digital Library, and Google Scholar. The results of the study have shown that AI can play an important role in enhancing the level of automation, which can reduce the time of detecting cyber threats up to 60 times. Despite the importance of AI in the CTI environment, there are some limitations to the adoption of AI in the CTI environment. The findings of this review have shown that there are four major themes, which include the role of AI in enhancing the level of automation, explainability, ethics, privacy, integration, and complexity.