Development of Conceptual Model for Performing Process Mining on Blockchain Data: A Cybersecurity Approach

The rise of smart cities has increased the need for more reliable, resilient, efficient, and sustainable network to protect sensitive data. In this study, we propose a Machine Learning (ML) and Process Mining-based solution for predicting and preventing cyberattacks in blockchain networks in smart cities. A conceptual model for identifying cyberattacks was put forth along with an analysis of the security of blockchain transactions. The blockchain network's security can be greatly enhanced by using ML and process mining techniques to spot fraudulent or malicious activity. Our results show that our solution can accurately predict cyber risk in blockchain networks and can be integrated into smart cities to enhance their cybersecurity measures. This study contributes to the growing field of using blockchain in smart cities, with a focus on cybersecurity, and provides a practical solution for predicting cyber risk in blockchain networks.