A Fuzzy Decision-Making Framework for Quantum-Enhanced Cybersecurity in Smart Cities

Abstract

Smart cities rely heavily on interconnected digital systems to provide efficient services in healthcare, transportation, energy, and other critical domains. However, these systems face increasing cybersecurity threats, and conventional security approaches often fail to address uncertainty and complexity. This chapter presents a fuzzy decision-making framework for quantum-enhanced cybersecurity in smart cities, which integrates cybersecurity data, quantum security capabilities, and expert-defined fuzzy rules. The framework processes uncertain inputs such as threat level, system vulnerability, data sensitivity, network criticality, and cost, transforming them into actionable security decisions. Through fuzzification, inference, aggregation, and defuzzification, the system recommends appropriate security strategies, including classical, hybrid, or quantum-enhanced solutions. Use case scenarios in smart healthcare, transportation, and energy grids illustrate how the framework adapts to varying risk levels, ensuring data privacy, operational continuity, and efficient resource allocation.