AI-Powered Solutions for Enhancing National Cybersecurity: Predictive Analytics and Threat Mitigation

Abstract

As the frequency and sophistication of cyberattacks continue to rise, the need for advanced solutions to strengthen national cybersecurity has never been more urgent. Artificial Intelligence (AI), particularly through predictive analytics, offers transformative potential in preemptively identifying, mitigating, and responding to cybersecurity threats. This paper explores the application of AI-powered solutions in enhancing national cybersecurity frameworks, with a focus on predictive analytics, machine learning (ML), and threat intelligence systems. The study examines how AI algorithms, including supervised learning, deep learning, and anomaly detection, can be integrated into national security infrastructures to anticipate cyber threats, identify vulnerabilities, and automate response mechanisms. Additionally, the role of AI in threat hunting, real-time monitoring, and incident response is evaluated. Through case studies and the application of predictive models, this paper demonstrates how AI can enhance the speed, accuracy, and efficiency of cybersecurity operations, ensuring a proactive defense against emerging cyber risks. By leveraging AI for enhanced threat mitigation, national cybersecurity strategies can evolve from reactive to proactive, significantly reducing the impact of cyber incidents and strengthening the resilience of critical national infrastructure.