AI-Driven Threat Intelligence: Anticipating Cyberattacks in Real-Time

Abstract

The article under consideration discusses how AI-based threat intelligence is used in the predictability of cyberattacks, with the emphasis on how AI technologies can be used to collect data, analyze it, and correlate it to improve cybersecurity strategies. The research takes a mixed methods approach, which is the qualitative study of case studies and quantitative data of real life applications. Some of the main conclusions are that AI can be utilized in early detection and real-time response, which will cause cyberattacks to have minimal effect. Nevertheless, there are still the challenges of false positives, data privacy, as well as scalability issues. The study highlights that the constant perfection of AI models is essential to enhance the accuracy and reliability. It is concluded that AI-based threat intelligence is an important resource that an organization should consider in its quest to actively fight cyber threats, although it is important to implement it carefully and continuously evaluate it to optimize its benefits. The research adds to the knowledge of intertwining AI and cybersecurity and provides useful information to both practitioners and researchers.