Mathematical and AI-Blockchain Integrated Framework for Strengthening Cybersecurity in National Critical Infrastructure

Abstract

This article examines the intersection between mathematical modeling, artificial intelligence (AI), and blockchain technology as a way of strengthening cybersecurity in national critical infrastructures (NCI). The increasing frequency and sophistication of cyber threats against vital infrastructures, such as electrical grids, healthcare information networks, and transportation infrastructures, creates the need to develop some innovative protective mechanisms. To solve these concerns, in the article the authors propose a hybrid framework that combines the AI-driven predictive analysis and the decentralized ledger capabilities of blockchain technology. Decentralized ledger technology (DLT) forms the backbone of secure and tamper-proof data management and machine learning algorithms are used to identify and predict emerging threats in real-time. By combining the immutability of the blockchain technology and the adaptive analytical capabilities of AI, this framework aims to improve the integrity of the data, maintain the privacy of it, and provide a fast-responding mechanism in the NCI environments. The paper outlines possible applications, lists the benefits that come with such applications, and addresses challenges inherent in the implementation of such an integrated system in order to provide a blueprint for future scholarly investigation and practical implementation.