The application of cybersecurity in smart city innovations: an AI aspect

Abstract

Internet of Things (IoT), Artificial Intelligence (AI), and Machine Learning (ML) have enabled "Smart Cities," opening up new municipal governance and civic participation prospects. Technological advances improve infrastructure, efficiency, and urban ecology. These complex systems pose cybersecurity risks that require new solutions for protecting information systems. This article creates digital twins using IoT, AI, and ML to study cybersecurity in Smart Cities (SCs). The IoT connects the city's transportation networks, services, and government offices to form a unified system. The system improves efficiency, decision-making, and robotics using AI and ML. This relationship boosts the economy, green behavior, and citizens' lives. Smart cities are subject to hacking, privacy breaches, and system disruptions due to their computer dependency. Modern urban areas face complicated safety problems due to IoT, AI, and ML. Most IoT devices lack security mechanisms, making them accessible to scammers. Biased ML and AI theories may affect results. This paper examines how virtual copies reduce supply chain cybersecurity risks. Simulations of actual commodities and infrastructure help model and assess supply chain vulnerabilities. These synthetic copies help us find weaknesses, simulate cyberattacks, and assess their effects. IoT, AI, and ML connected smart cities offer pros and cons. The paper recommends employing replicas to reduce cybersecurity risks and putting safety first in supply chain development and management.