块链
计算机科学
过程(计算)
计算机安全
光学(聚焦)
领域(数学)
网络威胁
操作系统
光学
纯数学
数学
物理
作者
Raneem Ahmed Mohamed,Gamal Kassem
标识
DOI:10.1109/smartcities4.056956.2023.10525756
摘要
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.
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