The rising deployment of nuclear-powered data centers offers a sustainable and high-capacity solution to meet the ever-growing demand for computing power. However, these facilities present unique cybersecurity challenges due to their complex infrastructure and critical role in national security and global digital infrastructure. This paper explores AI-enabled cybersecurity solutions to enhance the resilience of nuclear-powered data centers against sophisticated cyber threats. By leveraging machine learning models, such as anomaly detection and reinforcement learning, the proposed framework is capable of real-time threat detection, automated incident response, and system vulnerability analysis. The study also incorporates a hybrid approach combining AI with traditional security measures, ensuring comprehensive protection against both known and emerging threats. Experimental results demonstrate that the AI-driven solutions achieve high detection accuracy, faster response times, and improved system resilience, thereby safeguarding the integrity and availability of these critical infrastructures. The findings indicate that AI-enabled cybersecurity can significantly enhance the overall security posture of nuclear-powered data centers, paving the way for their secure and reliable integration into the global data ecosystem.
Anusooya et al. (Sat,) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: