Designing and localizing a novel cybersecurity model according to smart city digital infrastructure components (A Case Study of GreenWeb Co.)

Purpose: Today, the world is witnessing the evolution of smart cities. The emergence of these cities results from the application of information technology innovations, which, despite creating numerous economic and social opportunities, have introduced cybersecurity and privacy threats to citizens. Smart cities' successful transition to optimal performance depends on awareness of these threats and their impact. This study aims to provide a framework for identifying and evaluating cybersecurity criteria and examining their effect on cybersecurity performance in smart cities.Methodology: To achieve the study's practical purpose, a descriptive survey method was used to collect the necessary data. The criteria were identified through in-depth library research and surveys conducted via researcher-made questionnaires using the fuzzy Delphi method. Academic experts and relevant officials selected purposefully participated in the surveys. The importance of each criterion was determined using the fuzzy Best-Worst Multi-Criteria method. Subsequently, based on the digital infrastructure components of the smart city, the cybersecurity performance of the smart city was described according to the criteria identified in the previous step. The study hypotheses were then tested using Structural Equation Modeling based on the Partial Least Squares method.Findings: Analysis of the fitted model and research hypotheses revealed a positive and significant relationship between the variables of cybersecurity process re-engineering and cybersecurity actions with cybersecurity performance at a ۹۵% confidence level. Considering the value of the R² coefficient, it was observed that the variables of cybersecurity process re-engineering and cybersecurity actions collectively predicted ۷۲.۷% of the cybersecurity performance variable of the smart city.Originality/value: This article highlights the importance of cybersecurity in smart cities. It explains factors that affect cybersecurity and proposes a conceptual framework for providing cybersecurity services based on the digital infrastructure of the smart city. This study focuses on factors that occur before incidents, such as vulnerabilities and preventive measures. Future research should consider factors that occur after incidents, such as the actions taken and the recovery of digital systems.Purpose: Today, the world is witnessing the evolution of smart cities. The emergence of these cities results from the application of information technology innovations, which, despite creating numerous economic and social opportunities, have introduced cybersecurity and privacy threats to citizens. Smart cities' successful transition to optimal performance depends on awareness of these threats and their impact. This study aims to provide a framework for identifying and evaluating cybersecurity criteria and examining their effect on cybersecurity performance in smart cities. Methodology: To achieve the study's practical purpose, a descriptive survey method was used to collect the necessary data. The criteria were identified through in-depth library research and surveys conducted via researcher-made questionnaires using the fuzzy Delphi method. Academic experts and relevant officials selected purposefully participated in the surveys. The importance of each criterion was determined using the fuzzy Best-Worst Multi-Criteria method. Subsequently, based on the digital infrastructure components of the smart city, the cybersecurity performance of the smart city was described according to the criteria identified in the previous step. The study hypotheses were then tested using Structural Equation Modeling based on the Partial Least Squares method. Findings: Analysis of the fitted model and research hypotheses revealed a positive and significant relationship between the variables of cybersecurity process re-engineering and cybersecurity actions with cybersecurity performance at a ۹۵% confidence level. Considering the value of the R² coefficient, it was observed that the variables of cybersecurity process re-engineering and cybersecurity actions collectively predicted ۷۲.۷% of the cybersecurity performance variable of the smart city. Originality/value: This article highlights the importance of cybersecurity in smart cities. It explains factors that affect cybersecurity and proposes a conceptual framework for providing cybersecurity services based on the digital infrastructure of the smart city. This study focuses on factors that occur before incidents, such as vulnerabilities and preventive measures. Future research should consider factors that occur after incidents, such as the actions taken and the recovery of digital systems.

Keywords:

Smart City , Cybersecurity , Passive defense , Digital infrastructure , Business process re-engineering (BPR) , Structural equation modeling (SEM) , Fuzzy Best-Worst Multi-criteria method (FBWM)