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Affiliation(s)

Ageno School of Business, Golden Gate University, San Francisco 94105, California, USA

ABSTRACT

The national grid and other life-sustaining critical infrastructures face an unprecedented threat from prolonged blackouts, which could last over a year and pose a severe risk to national security. Whether caused by physical attacks, EMP (electromagnetic pulse) events, or cyberattacks, such disruptions could cripple essential services like water supply, healthcare, communication, and transportation. Research indicates that an attack on just nine key substations could result in a coast-to-coast blackout lasting up to 18 months, leading to economic collapse, civil unrest, and a breakdown of public order. This paper explores the key vulnerabilities of the grid, the potential impacts of prolonged blackouts, and the role of AI (artificial intelligence) and ML (machine learning) in mitigating these threats. AI-driven cybersecurity measures, predictive maintenance, automated threat response, and EMP resilience strategies are discussed as essential solutions to bolster grid security. Policy recommendations emphasize the need for hardened infrastructure, enhanced cybersecurity, redundant power systems, and AI-based grid management to ensure national resilience. Without proactive measures, the nation remains exposed to a catastrophic power grid failure that could have dire consequences for society and the economy.

KEYWORDS

National grid blackout, critical infrastructure security, EMP, cyberattack resilience, AI-powered grid protection, ML in energy security, power grid vulnerabilities, physical attacks on infrastructure, predictive maintenance for power grids, energy crisis and national security.

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