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Data Privacy and Cybersecurity in Wind Power Systems
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Author(s): Binastya Anggara Sekti (Universitas Esa Unggul, Indonesia)
Copyright: 2026
Pages: 32
Source title:
AI-Powered Analysis, Modeling, and Monitoring of Wind Energy Systems
Source Author(s)/Editor(s): Jackson J. Justo (University of Dar es Salaam, Dar es Salaam, Tanzania & ITMO University, St. Petersburg, Russia), Galina Demidova (Hangzhou Dianzi University, China & ITMO University, St. Petersburg, Russia), Francis A. Mwasilu (University of Dar es Salaam, Tanzania), Dmitry V. Lukichev (ITMO University, Russia)and Ramesh C. Bansal (University of Sharjah, Sharjah, UAE & University of Pretoria, Pretoria, South Africa)
DOI: 10.4018/979-8-3373-4159-0.ch009
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Abstract
The growing digitalization of wind power systems has intensified cybersecurity and data privacy challenges across modern renewable energy infrastructures. As AI, digital twins, and cloud-based platforms become integral to turbine monitoring and control, wind farms face expanding attack surfaces and increased vulnerability to malware, sensor spoofing, DDoS attacks, and supply chain breaches. These risks threaten operational continuity, grid stability, and the confidentiality of sensitive operational and geospatial data. Ensuring secure and privacy-compliant wind operations requires multi-layered protection that includes Zero Trust architectures, secure industrial protocols, robust identity and access management, encrypted communication channels, and strong AI governance. A comprehensive understanding of emerging threat vectors and resilient defense mechanisms is essential for safeguarding AI-powered wind energy ecosystems against evolving cyber and privacy risks.
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