From Voltage to Vulnerability: A Survey of Dynamic Security Risk Assessment Techniques in Smart Grids

From Voltage to Vulnerability: A Survey of Dynamic Security Risk Assessment Techniques in Smart Grids | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article From Voltage to Vulnerability: A Survey of Dynamic Security Risk Assessment Techniques in Smart Grids Mostafa Arjmand, Behzad Akbari, Hamid Reza Ghaeini This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7150779/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 11 Dec, 2025 Read the published version in International Journal of Information Security → Version 1 posted 11 You are reading this latest preprint version Abstract This paper presents a comprehensive analysis of dynamic risk assessment methods used in smart grid environments, with a particular focus on emerging approaches in artificial intelligence, mathematical modeling, and hybrid frameworks. We evaluate 44 recent publications (2016-2025) and analyze their primary analysis methods, application areas, risk assessment techniques, impact measurements, evaluation approaches, and implementation requirements. The analysis reveals three primary methodological categories: Artificial Intelligence and Machine Learning (AI/ML)-based approaches (55\%), mathematical model-based methods (20\%) and hybrid approaches (25%), with a clear trend towards integrated approaches that combine multiple methods while maintaining real-time assessment capabilities. Our multidimensional analysis framework examines the underlying methods, application domains, risk analysis techniques, impact measurements and evaluation approaches and reveals significant patterns in implementation strategies in different smart grid security contexts. The analysis of DRA methods for smart grid environments is a novel contribution that fills a gap in the existing literature, which typically deals with cybersecurity in general and does not focus on the dynamic aspects required for critical infrastructure protection. Dynamic Risk Assessment Cyber Security Smart Grid Critical Infrastructure Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 11 Dec, 2025 Read the published version in International Journal of Information Security → Version 1 posted Editorial decision: Revision requested 18 Sep, 2025 Reviews received at journal 12 Sep, 2025 Reviewers agreed at journal 31 Aug, 2025 Reviewers agreed at journal 28 Aug, 2025 Reviews received at journal 27 Aug, 2025 Reviewers agreed at journal 25 Aug, 2025 Reviewers agreed at journal 25 Aug, 2025 Reviewers invited by journal 25 Aug, 2025 Editor assigned by journal 18 Jul, 2025 Submission checks completed at journal 18 Jul, 2025 First submitted to journal 17 Jul, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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