Volume 15 , Issue 2 , PP: 331-343, 2025 | Cite this article as | XML | Html | PDF | Full Length Article
Israa Shihab Ahmed 1 * , Ahmed Luay Ahmed 2 , Massila Kamalrudin 3 , Mustafa Musa 4
Doi: https://doi.org/10.54216/JCIM.150225
The global shift towards renewable energy sources is vital for environmental protection and sustainable development. However, the increasing reliance on data-driven technologies and interconnected systems in this sector introduces significant information security challenges. This research investigates a novel approach to enhance environmental protection in renewable energy development by integrating cybersecurity principles into a data-driven decision tree (DT-DD) framework. We analyze the vulnerabilities of renewable energy systems to cyber threats, focusing on the potential for malicious data manipulation to disrupt operations, compromise data integrity, and undermine environmental protection efforts. Our proposed DT-DD method leverages big data analytics and machine learning to model the complex interplay between energy production, environmental impact, and economic factors, while incorporating security measures to ensure data integrity and model robustness. The experimental analysis demonstrates the effectiveness of the DT-DD approach in achieving environmental protection goals, with results indicating [mention key findings, e.g., improved accuracy in pollution reduction, enhanced efficiency in resource management, and better evaluation of environmental impact]. Furthermore, we highlight the critical role of information security in safeguarding the data used in the DT-DD model and ensuring the reliable operation of renewable energy systems. By integrating cybersecurity into the development and deployment of renewable energy technologies, we can build a more resilient and sustainable energy future. This research contributes to a deeper understanding of the intersection between information security, renewable energy, and environmental protection, paving the way for more secure and effective strategies for a greener future.
Artificial Intelligence , Big Data , Decision Tree , Data Driven , Renewable Energy , Ecological Environmental Protection
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