Theoretical Frameworks for the Role of Ai and Machine Learning in Water Cybersecurity: Insights From African and U.S. Applications

Abstract

This review paper explores the theoretical frameworks underpinning the application of Artificial Intelligence (AI) and Machine Learning (ML) in enhancing cybersecurity within the water sector, with a focus on both African and U.S. contexts. It delves into the unique cybersecurity challenges faced by the water sector, emphasizing the critical role of AI and ML in identifying, predicting, and mitigating cyber threats. The paper discusses the ethical considerations and regulatory frameworks influencing the deployment of these technologies alongside the technical, socioeconomic, and data privacy challenges encountered. Future directions and emerging trends in AI and ML that could impact water cybersecurity are examined, offering insights into potential research areas and strategies for overcoming existing barriers. This comprehensive review underscores the importance of integrating AI and ML into water cybersecurity strategies to safeguard critical water infrastructure.
 Keywords: Artificial Intelligence, Machine Learning, Water Cybersecurity, Ethical Considerations, Regulatory Frameworks, Emerging Trends.