Green Security: A Systematic Review on the Link Between AI-Driven Cybersecurity and Sustainability

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. However, the environmental implications of AIdriven 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, providing a structured classification of methodologies, application domains, sustainability objectives, and open challenges. Key challenges include the lack of standardized sustainability metrics in cybersecurity, the high energy demands of advanced security models, and the limited adoption of cross-layer and lifecycle-aware optimization techniques. Beyond technical analysis, the review contextualizes its findings within the United Nations Sustainable Development Goals (SDGs), particularly those related to responsible innovation, clean energy, and resilient infrastructure. The findings underscore the need for multi-objective optimization frameworks, lifecycle carbon accounting, and policy-driven strategies that collectively enhance cybersecurity robustness, privacy preservation, and environmental stewardship. This systematic review ultimately establishes a research agenda for the development of AI-based cybersecurity solutions that are not only secure and efficient but also environmentally responsible and aligned with global sustainability objectives.