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

Green Security: A Systematic Review on the Link Between AI-Driven Cybersecurity and Sustainability | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 3 September 2025 V1 Latest version Share on Green Security: A Systematic Review on the Link Between AI-Driven Cybersecurity and Sustainability Authors : Saeid Jamshidi 0000-0003-1612-529X [email protected] , Omar Abdul Wahab , and Martine Bellaïche Authors Info & Affiliations https://doi.org/10.22541/au.175693404.47705376/v1 362 views 227 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract 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. Supplementary Material File (ieee_cybersecurity_sustainability.pdf) Download 12.92 MB Information & Authors Information Version history V1 Version 1 03 September 2025 Copyright This work is licensed under a Non Exclusive No Reuse License. Keywords artificial intelligence (ai) cybersecurity energy efficiency internet of things (iot) sustainability sustainable development goals (sdgs) Authors Affiliations Saeid Jamshidi 0000-0003-1612-529X [email protected] View all articles by this author Omar Abdul Wahab View all articles by this author Martine Bellaïche View all articles by this author Metrics & Citations Metrics Article Usage 362 views 227 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Saeid Jamshidi, Omar Abdul Wahab, Martine Bellaïche. Green Security: A Systematic Review on the Link Between AI-Driven Cybersecurity and Sustainability. Authorea . 03 September 2025. DOI: https://doi.org/10.22541/au.175693404.47705376/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu . 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