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Cybersecurity Challenges in AI-Driven Energy Systems: Current and Future Prospects Concerning Ethical and Legal Provisions
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Author(s): Kanchan Chandar Tolani (Ramdeobaba University, Nagpur, India), A. Vijayalakshmi (Chaitanya Bharathi Institute of Technology, Hyderabad, India), Pritam Lanjewar (Datta Meghe Institute of Management Studies, Nagpur, India), Monali G. Dhote (Yeshwantrao Chavan College of Engineering, Nagpur, India), Saurabh Chandra (Bennett University, Greater Noida, India), Saquib Ahmed (Sharda University, India)and Bhupinder Singh (Sharda University, India)
Copyright: 2025
Pages: 14
Source title:
Leveraging AI for Innovative Sustainable Energy: Solar, Wind and Green Hydrogen
Source Author(s)/Editor(s): Hind Hammouch (University Sidi Mohamed Ben Abdellah, Morocco)and Laeeq Razzak Janjua (WSB University, Poland)
DOI: 10.4018/979-8-3373-0045-0.ch008
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Abstract
Artificial intelligence in energy systems has brought a significant improvement of efficiency, management and optimization making them dependable, there are also big concerns in the cybersecurity domain. A major worry is the risk of AI algorithms being influenced by data poisoning which is when bad actors introduce corrupted data to cause malfunctions on a system. AI-powered energy systems frequently connect thousands of IoT devices and every one of these represents a potential gateway to a system breach if not correctly protected. In addition, threats such as ransomware, phishing and Distributed Denial of Service (DDoS) attacks can compromise the integrity of energy management systems. Security of AI models and data, strong encryption protocols to ensure that these infra are secure from the cyber threat elites of today because of which we must build a real-time monitoring system too. Energy industry can prevent catastrophe by prioritizing cybersecurity.
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