AI-Driven Threat Detection and Response Systems for Secure National Infrastructure Networks: A Comprehensive Review

Abstract: Due to the increased complexity and damage of cyberattacks in this digital age, the security of national infrastructure networks has become a vital concern. However, a possible approach to improve the cybersecurity of these crucial networks is to incorporate artificial intelligence (AI) into threat detection and response systems; to rapidly evaluate large data sets, identify anomalies, and automate countermeasures to lessen the effects of cyberattacks. The impact, implementation and approaches for anomaly detection and response automation of AI-powered solutions for safeguarding national infrastructure are examined in this paper. Understanding how AI technologies are used to automate threat detection and response, reviewing the operational usefulness of AI in enhancing cybersecurity measures and evaluating the deployment of these systems in critical infrastructure settings were also examined. The study revealed that the speed and accuracy of threat detection and response are greatly increased by AI-powered systems. The automation capacity of AI can potentially reduce the need for human analysts, while also providing faster threat mitigation. Additionally, the usefulness of AI across sectors indicates its practicality in situations and how it may adapt in response to new threats. In conclusion, AI-driven threat detection and response systems are an important development in national infrastructure network cybersecurity. Therefore, by improving the capacity to recognize and address cyber-attacks these technologies can ultimately increase the overall resilience of national infrastructures.

Keywords: Artificial Intelligence (AI), Machine Learning, Threat Detection, Response Systems, Network Security

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