Green Security: A Systematic Review on the Link Between AI-Driven Cybersecurity and Sustainability
Saeid Jamshidi, Omar Abdul Wahab, Martine Bellaïche · 2025
The convergence of Artificial Intelligence (AI) and cybersecurity has significantly strengthened the protection of digital infrastructures, particularly in critical domains such as the Internet of Things (IoT), smart grids, and industrial control systems. Yet, the environmental implications of AI-driven security solutions remain underexplored, despite the growing imperative for sustainability in technology development. This paper presents a systematic review of contemporary research at the intersection of AI, cybersecurity, and sustainability, offering a structured classification of methodologies, application domains, and challenges. Key challenges are identified, e.g., the absence of standardized sustainability metrics in cybersecurity, the high energy demands of current security models, and the limited application of cross-layer optimization techniques. Moreover, beyond technical analysis, the review aligns its understanding with global sustainability priorities outlined in the United Nations Sustainable Development Goals (SDGs), particularly those related to responsible innovation, clean energy, and resilient infrastructure. Furthermore, the findings underscore the need for multi-objective optimization frameworks, lifecycle carbon accounting, and policy-driven strategies that jointly advance cybersecurity robustness and environmental stewardship. Besides, this systematic review sets a research agenda for the development of AI-based cybersecurity solutions that are not only secure and efficient but also aligned with global sustainability objectives.