Proactive Defense in a Converged Threat Environment: Leveraging Predictive Cyber Analytics to Safeguard the United States' Critical Infrastructure

The growing digitization and interconnectedness of national infrastructure systems have increased the attack surface for both cyber and physical threats, necessitating an increasing need to implement a forward-thinking, intelligence-driven strategy that identifies and mitigates problems before they arise. The purpose of this review research is to investigate the strategic and technical foundations of proactive defense mechanisms, with a particular emphasis on how predictive cyber analytics might be used to effectively protect critical infrastructure in the United States. From the study, predictive cyber analytics improve situational awareness and threat forecasting, allowing stakeholders to detect weak signals and preemptively neutralize attack efforts. Tools that utilize AI and large-scale data aggregation can potentially model attacker behaviour and automate anomaly detection at the edge and core of important systems. Furthermore, the integration of these tools is dependent on modular design, cross-sector interoperability, real-time data exchange, and governance structures that assure ethical AI use and transparent decision-making. Therefore, integrating predictive analytics into United States national defense strategy necessitates technological innovation, coordinated policy, standardized processes, and public-private collaboration.