AI-Powered Threat Intelligence: Automating Cyber Threat Analysis and Prediction

EasyChair Preprint 14114

Abstract

AI-powered Threat Intelligence (AITI) has emerged as a promising approach to automate and enhance the analysis and prediction of cyber threats. In this study, we explore the potential of AITI in addressing the challenges faced by organizations in dealing with the ever-evolving landscape of cyber threats. We examine how AI techniques can be leveraged to collect, analyze, and interpret vast amounts of data in real-time, allowing for more accurate threat identification and proactive mitigation strategies. We also discuss the implications of AITI on the roles and responsibilities of cybersecurity professionals, emphasizing the need for continuous learning and adaptation in this rapidly changing field. Through a comprehensive review of existing literature and case studies, we provide insights into the current state of AITI implementation, its benefits, and its limitations. Our findings suggest that AITI has the potential to revolutionize the way organizations detect, predict, and respond to cyber threats, ultimately enhancing their overall cybersecurity posture. However, we also highlight the ethical and privacy considerations that arise with the use of AI in cybersecurity and provide recommendations for addressing these concerns. Overall, this study contributes to the growing body of knowledge on AITI and provides practical guidance for organizations looking to leverage AI capabilities in their cybersecurity strategies.

Keyphrases: AI-powered Threat Intelligence (AITI), Cyber Threats, Cybersecurity

@booklet{EasyChair:14114,
  author    = {Ralph Shad and Peter Broklyn and Kaledio Potter},
  title     = {AI-Powered Threat Intelligence: Automating Cyber Threat Analysis and Prediction},
  howpublished = {EasyChair Preprint 14114},
  year      = {EasyChair, 2024}}