Cyber Kill Chain Analysis Using Artificial Intelligence

Abstract

Artificial Intelligence (AI) tools are promising multifaceted techniques for addressing the most mundane tasks for greater efficiency and high productivity. Cyber security space is one of the areas that AI is promising to revolutionize. This study will develop a conceptual and theoretical framework to support a research design that can simulate research in understanding how AI can be applied to Cyber Kill Chain phases. This study has reviewed 21 journal and conference articles mostly from IEEE Xplore database. An overview of the application of artificial intelligence (AI) in cybersecurity, particularly within the framework of the Cyber Kill Chain was provided in this study. It also emphasizes the limitations of traditional security approaches and the necessity for innovative and intelligent defense methodologies. The results of reviewing the relevant literatures discovered that the key components of cybersecurity, includes identity, asset management, automated configuration management, security control validation, governance, risk assessment, and vulnerability identification. A theoretical framework was developed which introduces the Cyber Kill Chain model with a Unified Kill Chain model to address its shortcomings. Application of AI in cybersecurity offers an optimistic solutions to address the evolving threat landscape. AI techniques, such as machine learning, anomaly detection, and behavioural analysis, have shown great potential in enhancing various aspects of cybersecurity.  However, challenges related to data quality, adversarial attacks, and privacy concerns need to be addressed for successful implementation. Further research and development are crucial to fully harness the power of AI in cybersecurity and stay ahead of evolving cyber threats.