Artificial Intelligence-Driven Optimization of Blockchain Scalability for Foundational Frameworks in Internet of Things Cybersecurity Architectures

Abstract

The fusion of Artificial Intelligence (AI) and Blockchain technology holds transformative potential for addressing scalability challenges in Internet of Things (IoT) cybersecurity architectures. This paper explores optimization frameworks utilizing AI to enhance blockchain scalability, ensuring robust and efficient IoT security systems. It synthesizes prior research and proposes a conceptual model leveraging AI techniques such as machine learning and neural networks. The analysis includes a literature review, technological advancements, and case studies demonstrating enhanced performance and scalability.